# មហាវិទ្យាល័យការសរសេរកូដសំរាប់ការសម្ភាសន៍ (Coding Interview University)


### បង្កើតដោយ: [@John Washam](https://github.com/jwasham)
### បកប្រែជាភាសារខ្មែរដោយ: [@Vortana Say](https://github.com/vsay01)

> ពីដំបូងខ្ញុំបង្កើតនេះជាបញ្ជីប្រធានបទត្រូវធ្វើខ្លីដើម្បីក្លាយជាវិស្វករអភិវឌ្ឍន៍កម្មវិធី ប៉ុន្តែវាបានកើនឡើងដល់បញ្ជីធំដែលអ្នកបានឃើញសព្វថ្ងៃនេះ។ បន្ទាប់ពីឆ្លងកាត់គំរោងសិក្សានេះ    [ ខ្ញុំបានក្លាយ ជាវិស្វករអភិវឌ្ឍន៍កម្មវិធីនៅអាមាហ្សូន (Amazon)](https://startupnextdoor.com/ive-been-acquired-by-amazon/?src=ciu)
> អ្នកប្រហែលជាមិនចាំបាច់សិក្សាច្រេីនដូចខ្ញុំទេ។ ទោះយ៉ាងណាក៏ដោយអ្វីគ្រប់យ៉ាងដែលអ្នកត្រូវការគឺនៅទីនេះ។
>
> ខ្ញុំបានសិក្សាប្រហែលជា ៨ ទៅ ១២ ម៉ោងក្នុងមួយថ្ងៃអស់រយៈពេលជាច្រើនខែ។ អ្នកអាចអានារឿងរបស់ខ្ញុំ៖ [ហេតុអ្វីខ្ញុំសិក្សាពេញម៉ោងរយៈពេល ៨ ខែសំរាប់ការសំភាសន៍ហ្គូហ្គល](https://medium.freecodecamp.org/why-i-studied-full-time-for-8-months-for-a-google-interview-cc662ce9bb13)
>
> ចំណុចដែលបានរាយនៅទីនេះនឹងជួយអ្នករៀបចំការសំភាសន៍បច្ចេកទេសនៅក្រុមហ៊ុនកម្មវិធីណាមួយ។
> រាប់បញ្ចូលទាំងក្រុមហ៊ុនធំៗដូចជា Amazon, Facebook, Google និង Microsoft ។
>
> សូមសំណាងល្អដល់អ្នក!

<details>
<summary>ការបកប្រែ៖</summary>

- [ភាសារចិន - 中文版本](translations/README-cn.md)
- [ភាសារវៀតណាម - Tiếng Việt - Vietnamese](translations/README-vi.md)
- [ភាសារអេស្ប៉ាញ - Español](translations/README-es.md)
- [ភាសារព័រទុយហ្កាល់ - Português Brasileiro](translations/README-ptbr.md)
- [ភាសារប៉ូឡូញ - Polish](translations/README-pl.md)

</details>

<details>
<summary>ភាសារដែលកំពុងបកប្រែ:</summary>

- [हिन्दी](https://github.com/jwasham/coding-interview-university/issues/81)
- [עברית](https://github.com/jwasham/coding-interview-university/issues/82)
- [Bahasa Indonesia](https://github.com/jwasham/coding-interview-university/issues/101)
- [Arabic](https://github.com/jwasham/coding-interview-university/issues/98)
- [Turkish](https://github.com/jwasham/coding-interview-university/issues/90)
- [French](https://github.com/jwasham/coding-interview-university/issues/89)
- [Russian](https://github.com/jwasham/coding-interview-university/issues/87)
- [Ukrainian](https://github.com/jwasham/coding-interview-university/issues/106)
- [Korean(한국어)](https://github.com/jwasham/coding-interview-university/issues/118)
- [Telugu](https://github.com/jwasham/coding-interview-university/issues/117)
- [Urdu](https://github.com/jwasham/coding-interview-university/issues/140)
- [Thai](https://github.com/jwasham/coding-interview-university/issues/156)
- [Greek](https://github.com/jwasham/coding-interview-university/issues/166)
- [Italian](https://github.com/jwasham/coding-interview-university/issues/170)
- [Malayalam](https://github.com/jwasham/coding-interview-university/issues/239)
- [Japanese (日本語)](https://github.com/jwasham/coding-interview-university/issues/257)

</details>

---

## តារាងមាតិកា

- [តើវាគឺជាអ្វី?](#what-is-it)
- [ហេតុអ្វីប្រើវា?](#why-use-it)
- [របៀបប្រើវា](#how-to-use-it)
- [កុំមានអារម្មណ៍ថាអ្នកមិនឆ្លាតគ្រប់គ្រាន់](#dont-feel-you-arent-smart-enough)
- [ធនធានវីដេអូ](#about-video-resources)
- [ដំណើរការសម្ភាសន៍ និង ការត្រៀមសម្ភាសន៍ទូទៅ](#interview-process--general-interview-prep)
- [ជ្រើសរើសភាសាមួយសម្រាប់ការសម្ភាសន៍](#pick-one-language-for-the-interview)
- [បញ្ជីសៀវភៅ](#book-list)
- [មុនពេលអ្នកចាប់ផ្តើម](#before-you-get-started)
- [អ្វីដែលអ្នកនឹងមិនឃើញ](#what-you-wont-see-covered)
- [ចំណេះដឹងជាមុនដែលគួរមាន](#prerequisite-knowledge)
- [ផែនការប្រចាំថ្ងៃ](#the-daily-plan)
- [ភាពស្មុគស្មាញនៃក្បួនដោះស្រាយ / Big-O / ការវិភាគ អាសុីមតុតិច (Asymptotic analysis)](#algorithmic-complexity--big-o--asymptotic-analysis)
- [Data Structures](#data-structures)
    - [Arrays](#arrays)
    - [Linked Lists](#linked-lists)
    - [Stack](#stack)
    - [Queue](#queue)
    - [Hash table](#hash-table)
- [ចំណេះដឹងបន្ថែម](#more-knowledge)
    - [Binary search](#binary-search)
    - [Bitwise operations](#bitwise-operations)
- [Trees](#trees)
    - [Trees - កំណត់សំគាល់ និង ប្រវត្តិ](#trees---notes--background)
    - [Binary search trees: BSTs](#binary-search-trees-bsts)
    - [Heap / Priority Queue / Binary Heap](#heap--priority-queue--binary-heap)
    - balanced search trees (គំនិតទូទៅ តែពុំមែនព័ត៌មានលម្អិតទេ)
    - traversals: preorder, inorder, postorder, BFS, DFS
- [Sorting](#sorting)
    - selection
    - insertion
    - heapsort
    - quicksort
    - merge sort
- [Graphs](#graphs)
    - directed
    - undirected
    - adjacency matrix
    - adjacency list
    - traversals: BFS, DFS
- [ចំណេះដឹងបន្ថែមទៀត](#even-more-knowledge)
    - [Recursion](#recursion)
    - [Dynamic Programming](#dynamic-programming)
    - [Object-Oriented Programming](#object-oriented-programming)
    - [Design Patterns](#design-patterns)
    - [Combinatorics (n choose k) & Probability](#combinatorics-n-choose-k--probability)
    - [NP, NP-Complete and Approximation Algorithms](#np-np-complete-and-approximation-algorithms)
    - [Caches](#caches)
    - [Processes and Threads](#processes-and-threads)
    - [Testing](#testing)
    - [Scheduling](#scheduling)
    - [String searching & manipulations](#string-searching--manipulations)
    - [Tries](#tries)
    - [Floating Point Numbers](#floating-point-numbers)
    - [Unicode](#unicode)
    - [Endianness](#endianness)
    - [Networking](#networking)
- [System Design, Scalability, Data Handling](#system-design-scalability-data-handling) (if you have 4+ years experience)
- [ពិនិត្យចុងក្រោយ](#final-review)
- [អនុវត្តសំណួរសរសេរកូដ](#coding-question-practice)
- [លំហាត់សរសេរកូដ / បញ្ហា](#coding-exerciseschallenges)
- [នៅពេលអ្នកជិតដល់ការសំភាសន៍](#once-youre-closer-to-the-interview)
- [ប្រវត្តិរូបសង្ខេបរបស់អ្នក](#your-resume)
- [ត្រូវគិតអំពីពេលសម្ភាសន៍មកដល់](#be-thinking-of-for-when-the-interview-comes)
- [មានសំណួរសម្រាប់អ្នកសម្ភាសន៍យេីង](#have-questions-for-the-interviewer)
- [នៅពេលដែលទទួលបានការងារធ្វើ](#once-youve-got-the-job)

---

## What is it? 
## តើវាគឺជាអ្វី?

នេះគឺជាគំរោងសិក្សារបស់ខ្ញុំដែលមានរយៈពេលជាច្រើនខែសំរាប់ការរៀនក្លាយពីអ្នកបង្កើតគេហទំព័រ (បង្រៀនដោយខ្លួនឯង និង មិនមានសញ្ញាប័ត្រ
វិទ្យាសាស្ត្រកុំព្យូទ័រ) រហូតដល់ក្លាយជាវិស្វករអភិវឌ្ឍន៍កម្មវិធីសំរាប់ក្រុមហ៊ុនធំ។!

![ការសរសេរកូដនៅលើក្ដារខៀន - ពីតំបន់ Silicon Valley របស់ HBO](https://d3j2pkmjtin6ou.cloudfront.net/coding-at-the-whiteboard-silicon-valley.png)

នេះមានន័យថាសម្រាប់ "វិស្វករអភិវឌ្ឍន៍កម្មវិធីថ្មី" ឬអ្នកដែលប្តូរពី
ការអភិវឌ្ឍន៍កម្មវិធី / អ្នកបង្កេីតវេបសាយ (ដែលត្រូវការចំណេះដឹងផ្នែកវិទ្យាសាស្ត្រកុំព្យូទ័រ) ។ ប្រសិនបើអ្នកមាន
បទពិសោធជាច្រើនឆ្នាំក្នុងការអភិវឌ្ឍន៍កម្មវិធី នោះអ្នកអាចនឹងរំពឹងថាមានបទសម្ភាសន៍ពិបាក។

ប្រសិនបើអ្នកមានបទពិសោធន៍អភិវឌ្ឍន៍កម្មវិធី ឬ វេបសាយច្រើនឆ្នាំ សូមកត់សម្គាល់ថាក្រុមហ៊ុនធំ ៗ ដូចជាហ្គូហ្គោល(Google) អាម៉ាហ្សូន (Amazon)
ហ្វេសប៊ុក (Facebook) និង ម៉ៃក្រូសូហ្វ (Microsoft) មានទស្សនៈថាវិស្វករអភិវឌ្ឍន៍កម្មវិធី ខុសគ្នាពីអ្នកបង្កេីតកម្មវិធី ឬ ការអភិវឌ្ឍន៍គេហទំព័រវេបសាយ ហើយពួកគេត្រូវការចំណេះដឹងផ្នែកវិទ្យាសាស្ត្រកុំព្យូទ័រ។

ប្រសិនបើអ្នកចង់ក្លាយជាវិស្វករដែលអាចទុកចិត្តបានឬវិស្វករប្រតិបត្តិការសូមសិក្សាបន្ថែមពីបញ្ជីជម្រើស (បណ្តាញ និង សុវត្ថិភាព) ។

---

### Why use it? 
## ហេតុអ្វីប្រើវា?

នៅពេលដែលខ្ញុំចាប់ផ្តើមគំរោងនេះ ខ្ញុំមិនដឹងពី stack, heap, Big-O, trees និង មិនដឹងរបៀបឆ្លងកាត់ក្រាហ្វ។ ប្រសិនបើខ្ញុំត្រូវសរសេរកូដដោះស្រាយ Sort ខ្ញុំអាចប្រាប់អ្នកថាវានឹងមិនល្អទេ។

Data Structure ទាំងអស់ដែលខ្ញុំធ្លាប់បានប្រើត្រូវបានបង្កើតឡើងមកជាមួយភាសា ហើយខ្ញុំមិនដឹងពីរបៀប និង ដំណេីរការដែល Data Structure។ ខ្ញុំមិនដែលត្រូវគ្រប់គ្រង Programming Memory ទេលុះត្រាតែកម្មវិធីខ្ញុំសរសេរមានបញ្ហា "អស់ Memory" ហើយបន្ទាប់មកខ្ញុំត្រូវរកដំណោះស្រាយបណ្តោះអាសន្ន។ ខ្ញុំបានប្រើ Multidiemsional arrays ពីរបីនៅក្នុងជីវិតរបស់ខ្ញុំ និង រាប់ពាន់នៃ Associate arrays ប៉ុន្តែខ្ញុំមិនដែលបង្កើត Data Structure ពីដំបូងឡើយ។

វាជាផែនការវែង។ វាអាចចំណាយពេលច្រើនខែ។ ប្រសិនបើអ្នកធ្លាប់ស្គាល់រឿងនេះរួចហើយវានឹងនាំអ្នកចំណាយពេលតិចជាងមុន។

---

### How to use it?
## របៀបប្រើវា


អ្វីគ្រប់យ៉ាងខាងក្រោមគឺជាគ្រោង អ្នកគួរតែដោះស្រាយតាមលំដាប់ពីលើចុះក្រោម។

ខ្ញុំកំពុងប្រើសញ្ញាសម្គាល់ពិសេសរបស់ GitHub រួមទាំងបញ្ជីភារកិច្ចដើម្បីពិនិត្យមើលវឌ្ឍនភាពការងារខ្ញុំ។

**បង្កើតសាខាថ្មី ដូច្នេះអ្នកអាចពិនិត្យមើលដូចនេះគ្រាន់តែដាក់សញ្ញា x ក្នុងតង្កៀប៖ [x]**


ដាក់សាខាមួយ ហើយធ្វើតាមពាក្យបញ្ជាខាងក្រោម

`git checkout -b progress`

`git remote add jwasham https://github.com/jwasham/coding-interview-university`

`git fetch --all`

គូសសញ្ញា X ក្នុងប្រអប់ទាំងអស់បន្ទាប់ពីអ្នកបានបញ្ចប់ការកែសម្រួល
`git add .`

`git commit -m "Marked x"`

`git rebase jwasham/master`

`git push --force`

[ព័ត៌មានបន្ថែមអំពីសញ្ញាសម្គាល់ Github]](https://guides.github.com/features/mastering-markdown/#GitHub-flavored-markdown)

---

### Don't feel you aren't smart enough
## កុំមានអារម្មណ៍ថាអ្នកមិនឆ្លាតគ្រប់គ្រាន់

- វិស្វករអភិវឌ្ឍន៍កម្មវិធីដែលទទួលបានជោគជ័យគឺឆ្លាត ប៉ុន្តែមនុស្សជាច្រើនមានអារម្មណ៍ដែលពួកគេមិនឆ្លាតគ្រប់គ្រាន់។
- [រឿងរបស់អ្នកសរសេរកម្មវិធីដែលមានទេពកោសល្យ](https://www.youtube.com/watch?v=0SARbwvhupQ)
- [វាមានគ្រោះថ្នាក់ក្នុងការទៅតែម្នាក់ឯង: ការប្រយុទ្ធនឹងសត្វចម្លែកដែលចេះបំបាំងកាយនៅក្នុងបច្ចេកវិទ្យា](https://www.youtube.com/watch?v=1i8ylq4j_EY)

---

### About Video Resources
## ធនធានវីដេអូ

វីដេអូខ្លះអាចប្រើបានតែតាមរយៈការចុះឈ្មោះចូលរៀនវគ្គ Coursera ឬ EdX ប៉ុណ្ណោះ។ ទាំងនេះត្រូវបានគេហៅថា MOOCs ។
ពេលខ្លះថ្នាក់រៀនមិននៅក្នុងវគ្គដូច្នេះអ្នកត្រូវរង់ចាំពីរបីខែសិន។

ខ្ញុំសូមកោតសរសើរចំពោះជំនួយរបស់អ្នកក្នុងការបន្ថែមប្រភពសាធារណៈដែលអាចរកបានដោយឥតគិតថ្លៃជានិច្ចដូចជាវីដេអូយូធ្យូប (YouTube) ដើម្បីភ្ជាប់វីដេអូវគ្គសិក្សាតាមអ៊ីនធឺណិត។

ខ្ញុំចូលចិត្តប្រើការបង្រៀនសាកលវិទ្យាល័យ។
    
---

### Interview Process & General Interview Prep
## ដំណើរការសំភាសន៍និងកម្មវិធីសម្ភាសន៍ទូទៅ

- [ ] [ABC: តែងតែសរសេរកូដ](https://medium.com/always-be-coding/abc-always-be-coding-d5f8051afce2#.4heg8zvm4)
- [ ] [ការប្រេីប្រាស់ក្តារខៀន](https://medium.com/@dpup/whiteboarding-4df873dbba2e#.hf6jn45g1)
- [ ] [ការប្រេីប្រាស់ក្តារខៀនមានប្រសិទ្ធិភាពក្នុងពេលសម្ភាសន៍កម្មវិធី](http://www.coderust.com/blog/2014/04/10/effective-whiteboarding-during-programming-interviews/)
- [ ] [ជ្រើសរើសបុគ្គលិកជំនាញបច្ចេកវិទ្យា](https://www.youtube.com/watch?v=N233T0epWTs)
- [ ] វិធីរកការងារនៅក្រុមហ៊ុនធំ ៤៖
    - [ ] [របៀបរកការងារធ្វើនៅក្រុមហ៊ុនធំ ៤ - Amazon, Facebook, Google និង Microsoft (មានវីដេអូ)](https://www.youtube.com/watch?v=YJZCUhxNCv8)
- [បំបែកការសម្ភាសន៍ការសរសេរកូដ ១៖
    - [ ] [ហ្គេលឡេអិលម៉ាកឌូវែល (Gayle L McDowell) - បំបែកការសម្ភាសន៍ការសរសេរកូដ (វីដេអូ)](https://www.youtube.com/watch?v=rEJzOhC5ZtQ)
    - [ ] [បំបែកបទសម្ភាសន៍នៃការសរសេរកូដជាមួយអ្នកនិពន្ធហ្គេលឡាឡាក់មែនម៉ាកម៉ាកឌូវែល (Gayle Laakmann McDowell)  (វីដេអូ)](https://www.youtube.com/watch?v=aClxtDcdpsQ)
- [ ] បំបែកបទសម្ភាសន៍កូដហ្វេសប៊ុក
    - [ ] [វិធីសាស្រ្ត](https://www.youtube.com/watch?v=wCl9kvQGHPI)
    - [ ] [ពន្យល់ពីបញ្ហា](https://www.youtube.com/watch?v=4UWDyJq8jZg)
- [ ] វគ្គសិក្សាត្រៀម:
    - [ ] [សំភាសន៍វិស្វករអភិវឌ្ឍន៍កម្មវិធី (មិនបានបង់ប្រាក់)](https://www.udemy.com/software-engineer-interview-unleashed)៖
        - រៀនពីរបៀបដើម្បីត្រៀមខ្លួនសម្រាប់ការសម្ភាសន៍វិស្វករអភិវឌ្ឍន៍កម្មវិធីពីអ្នកសំភាសន៍របស់ហ្គូហ្គោល (Google) ។
    - [ ] [Python សម្រាប់រចនាសម្ព័ន្ធទិន្នន័យក្បួនដោះស្រាយនិងសំភាសន៍ (វគ្គសិក្សាបង់លុយ)](https://www.udemy.com/python-for-data-structures-algorithms-and-interviews/)៖
        - វគ្គសិក្សាសំភាសន៍ Python ដែលផ្តោតលើរចនាសម្ព័ន្ធទិន្នន័យក្បួនដោះស្រាយ ការសំភាសន៍សាកល្បងនិងច្រើនទៀត។
    - [ ] [ការណែនាំអំពីរចនាសម្ព័ន្ធទិន្នន័យនិងក្បួនដោះស្រាយដោយប្រើ Python (វគ្គសិក្សាឥតគិតថ្លៃរបស់ Udacity)](https://www.udacity.com/course/data-structures-and-algorithms-in-python--ud513)៖
        - រចនាសម្ព័នធ័រណេតនិងអ័រហ្គ្រែនដោយឥតគិតថ្លៃ។
    - [ ] [រចនាសម្ព័នទិន្នន័យនិងក្បួនដោះស្រាយ! (Udacity បង់ Nanodegree)](https://www.udacity.com/course/data-structures-and-algorithms-nanodegree--nd256)៖
        - ទទួលបានការអនុវត្តជាក់ស្តែងជាមួយនឹងរចនាសម្ព័ន្ធទិន្នន័យជាង ១០០ លំហាត់ និងការណែនាំពីអ្នកបងៀនដើម្បីជួយរៀបចំអ្នកសម្រាប់ការសម្ភាសន៍ និង ដាក់ការងារ។
        
---

### Pick One Language for the Interview
## ជ្រើសរើសភាសាមួយសម្រាប់ការសម្ភាសន៍

អ្នកអាចប្រើភាសាដែលអ្នកមានភាពងាយស្រួលក្នុងការសរសេរកូដសំភាសន៍ប៉ុន្តែសម្រាប់ក្រុមហ៊ុនធំ ៗ ទាំងនេះគឺជាជំរើសដ៏រឹងមាំ៖

- C ++
- Java
- Python

អ្នកក៏អាចប្រើរបស់ទាំងនេះដែរប៉ុន្តែត្រូវអានជាមុនសិន។ វាអាចមានការនិយាយតៗគ្នា៖

- JavaScript
- Ruby

នេះគឺជាអត្ថបទមួយដែលខ្ញុំបានសរសេរអំពីការជ្រើសរើសភាសាសម្រាប់ការសម្ភាសន៍៖ [ជ្រើសរើសយកភាសាមួយសម្រាប់ការសម្ភាសន៍សរសេរកូដ](https://startupnextdoor.com/important-pick-one-language-for-the-coding-interview/)

អ្នកគួររេីសភាសាដែលអ្នកទំលាប់ជាមួយ និង មានចំណេះដឹង។

សូមអានបន្ថែមអំពីជំរើស៖
- http://www.byte-by-byte.com/choose-the-right-language-for-your-coding-interview/
- http://blog.codingforinterviews.com/best-programming-language-jobs/

[មើលធនធានភាសានៅទីនេះ](programming-language-resources.md)

អ្នកនឹងឃើញការរៀន C, C ++ និង Python ខាងក្រោមព្រោះខ្ញុំកំពុងរៀន។ មានសៀវភៅពីរបីដែលពាក់ព័ន្ធសូមមើលនៅខាងក្រោម។
        
---

### Book List
## បញ្ជីសៀវភៅ

នេះគឺជាបញ្ជីខ្លីជាងអ្វីដែលខ្ញុំបានប្រើ។ នេះត្រូវបានសង្ខេបដើម្បីជួយសន្សំសំចៃពេលវេលារបស់អ្នក។

---

### Interview Prep
## ត្រៀមការសម្ភាសន៍

- [ ] [សំភាសន៍ការសរសេរកម្មវិធីបង្ហាញ: ការសរសេរកូដវិធីរបស់អ្នកតាមរយៈការសំភាសន៍, បោះពុម្ពលើកទី ៤](https://www.amazon.com/Programming-Interviews-Exposed-Through-Interview/dp/111941847X/)
    - ចម្លើយសរសេរ C++ និង Java
    - នេះគឺជាសមដ៏ល្អសម្រាប់ការបំបែកសំភាសន៍កូដ
    - មិនពិបាកពេកទេ បញ្ហាភាគច្រើនប្រហែលជាងាយស្រួលជាងអ្វីដែលអ្នកបានឃើញក្នុងបទសម្ភាសន៍ (ពីអ្វីដែលខ្ញុំបានអាន)
- [ ] [ការសំភាសន៍ការសរសេរកូដការបោះពុម្ពលើកទី ៦](http://www.amazon.com/Cracking-Coding-Interview-6th-Programming/dp/0984782850/)
    - ចម្លើយនសរសេរជា Java
    
---

### If you have tons of extra time:
## ប្រសិនបើអ្នកមានពេលវេលាបន្ថែមច្រេីន

ជ្រើសរើសមួយ:

- [ ] [ធាតុផ្សំនៃបទសម្ភាសន៍សរសេរកម្មវិធី (កំណែ C ++)](https://www.amazon.com/Elements-Programming-Interviews-Insiders-Guide/dp/1479274836)
- [ ] [ធាតុផ្សំនៃការសំភាសន៍សរសេរកម្មវិធីក្នុង Python](https://www.amazon.com/Elements-Programming-Interviews-Python-Insiders/dp/1537713949/)
- [ ] ធាតុនៃការសំភាសន៍សរសេរកម្មវិធី (កំណែ Java)
    - [សៀវភៅ](https://www.amazon.com/Elements-Programming-Interviews-Java-Insiders/dp/1517435803/)
    - [គម្រោង - វិធីសាស្រ្ត Stub និងករណីតេស្តិ៍សម្រាប់រាល់បញ្ហាក្នុងសៀវភៅ](https://github.com/gardncl/elements-of-programming-interviews)

---

### Language Specific
## ភាសាជាក់លាក់

**អ្នកត្រូវជ្រើសរើសភាសាសំរាប់សំភាសន៍ (សូមមើលខាងលើ) ។**

នេះជាអ្នីដែលខ្ញុំគិតថាអ្នកគួរមេីល។ ខ្ញុំមិនមានធនធានសម្រាប់ភាសាទាំងអស់ទេ។ ខ្ញុំស្វាគមន៍ការដាក់បន្ថែមពីអ្នក។

ប្រសិនបើអ្នកអានចំណុចមួយក្នុងចំណោមចំណុចទាំងនេះអ្នកគួរតែមានចំនេះដឹង Data Structure និងចំណេះដឹងអំពីក្បួនដោះស្រាយ (Algorithm) ដែលអ្នកត្រូវចាប់ផ្តើមធ្វើបញ្ហាសរសេរកូដ។

**អ្នកអាចរំលងការបង្រៀនវីដេអូទាំងអស់នៅក្នុងគម្រោងនេះ** លើកលែងតែអ្នកចង់ពិនិត្យឡើងវិញ។

[ធនធានភាសាជាក់លាក់នៅទីនេះ។](programming-language-resources.md)

---

## C++

ខ្ញុំមិនបានអានទាំងពីរនេះទេ ប៉ុន្តែវាត្រូវបានវាយតម្លៃនិងសរសេរយ៉ាងខ្ពស់ដោយ Sedgewick ។ គាត់អស្ចារ្យណាស់។

- [ ] [វិធីដោះស្រាយក្នុង C++, ផ្នែក ១-៤៖ មូលដ្ឋានគ្រឹះរចនាសម្ព័ន្ធទិន្នន័យ (Data Structure) តម្រៀប (Sort) ស្វែងរក (Searching)](https://www.amazon.com/Algorithms-Parts-1-4-Fundamentals-Structure/dp/0201350882/)
- [ ] [វិធីដោះស្រាយក្នុង C++ ភាគ ៥៖ ក្បួនដោះស្រាយក្រាហ្វិច](https://www.amazon.com/Algorithms-Part-Graph-3rd-Pt-5/dp/0201361183/)

ប្រសិនបើអ្នកមានអនុសាសន៍ល្អប្រសើរសម្រាប់ C++ សូមប្រាប់ខ្ញុំឱ្យដឹង។ រកមើលធនធានទូលំទូលាយ។

---

## Java

- [ ] [វិធីដោះស្រាយ (Sedgewick និង Wayne)](https://www.amazon.com/Algorithms-4th-Robert-Sedgewick/dp/032157351X/)
    - វីដេអូដែលមានមាតិកាសៀវភៅ (និង Sedgewick!) លើវគ្គសិក្សា៖
        - [ក្បួនដោះស្រាយ I](https://www.coursera.org/learn/algorithms-part1)
        - [ក្បួនដោះស្រាយទី ២](https://www.coursera.org/learn/algorithms-part2)

រឺ៖

- [ ] [រចនាសម្ព័ន្ធទិន្នន័យ (Data Structure) និងក្បួនដោះស្រាយ Java](https://www.amazon.com/Data-Structures-Algorithms-Michael-Goodrich/dp/1118771338/)
    - ដោយហ្គ្រីដល (Goodrich), តាតសាសៀ (Tamassia), ហ្គោវីស (Goldwasser)
    - អត្ថបទសម្រាប់វគ្គសិក្សាសំរាប់ថ្នាក់ដំបូងរបស់វិទ្យាសាស្ត្រកុំព្យូទ័រនៅឯ UC Berkeley
    - សូមមើលរបាយការណ៍សៀវភៅរបស់ខ្ញុំស្តីពីកំណែ Python ខាងក្រោម។ សៀវភៅនេះមានប្រធានបទដូចគ្នា។

---

## Python
- [ ] [រចនាសម្ព័ន្ធទិន្នន័យ (Data Structure) និងក្បួនដោះស្រាយ (Algorithm) ក្នុង Python](https://www.amazon.com/Structures-Algorithms-Python-Michael-Goodrich/dp/1118290275/)
    - ដោយហ្គ្រីដល (Goodrich), តាតសាសៀ (Tamassia), ហ្គោវីស (Goldwasser)
    - ខ្ញុំចូលចិត្តសៀវភៅនេះ។ វាគ្របដណ្តប់អ្វីៗគ្រប់យ៉ាងនិងច្រើនទៀត។
    - លេខកូដព្យញ្ជនៈ
    - របាយការណ៍សៀវភៅរបស់ខ្ញុំ៖ https://startupnextdoor.com/book-report-data-structures-and-al algorithms-in-python/
    
---

### Before you Get Started
## មុនពេលអ្នកចាប់ផ្តើម

បញ្ជីនេះបានកើនឡើងអស់រយៈពេលជាច្រើនខែហើយ ។

នេះគឺជាកំហុសមួយចំនួនដែលខ្ញុំបានធ្វើដូច្នេះអ្នកនឹងមានបទពិសោធប្រសើរជាងមុន។

### 1. អ្នកនឹងមិនចងចាំវាទាំងអស់

ខ្ញុំបានមើលវីដេអូជាច្រើនម៉ោងនិងកត់ចំណាំគួរអោយចង់សើច ហើយប៉ុន្មានខែក្រោយមកមានរឿងជាច្រើនដែលខ្ញុំមិនចាំ។ ខ្ញុំចំណាយពេល ៣ ថ្ងៃទៀត
តាមរយៈកំណត់ចំណាំរបស់ខ្ញុំនិងធ្វើប័ណ្ណបញ្ជាក់ដូច្នេះខ្ញុំអាចពិនិត្យមើលឡើងវិញ។

សូមមេត្តាអានដូច្នេះអ្នកនឹងមិនធ្វើឱ្យខ្ញុំខុសទេ។

[រក្សាចំណេះដឹងវិទ្យាសាស្ត្រកុំព្យូទ័រ](https://startupnextdoor.com/retaining-computer-science-knowledge/) ។

វគ្គសិក្សាដែលបានណែនាំដល់ខ្ញុំ (មិនបានសិក្សាវាទេ)៖ [ការរៀនពីរបៀបរៀន](https://www.coursera.org/learn/learning-how-to-learn)

### 2. ប្រើកាតបង្ហាញ

ដើម្បីដោះស្រាយបញ្ហា ខ្ញុំបានបង្កើតវេបសាយកាតតូចមួយដែលខ្ញុំអាចបន្ថែមកាតចំនួន ២ ប្រភេទគឺទូទៅនិងលេខកូដ។
កាតនីមួយៗមានទ្រង់ទ្រាយខុសៗគ្នា។

ខ្ញុំបានបង្កើតវេបសាយសំរាប់ទូរស័ព្ទដំបូងមួយ ដូច្នេះខ្ញុំអាចពិនិត្យមើលឡើងវិញនៅលើទូរស័ព្ទ និង ថេប្លេតរបស់ខ្ញុំទោះបីខ្ញុំនៅទីណាក៏ដោយ។

អ្នកអាចបង្កេីតដោយឥតគិតថ្លៃ៖

- [បណ្តាញឃ្លាំងផ្ទុកកាតឡើងវិញ](https://github.com/jwasham/computer-science-flash-cards)
- [មូលដ្ឋានទិន្នន័យកាតរបស់ខ្ញុំ (កាតចាស់ - ១២០០ កាត)](https://github.com/jwasham/computer-science-flash-cards/blob/master/cards-jwasham.db)៖
- [ប្រព័ន្ធទិន្នន័យកាតរបស់ខ្ញុំ (កាតថ្មី - ១៨០០)](https://github.com/jwasham/computer-science-flash-cards/blob/master/cards-jwasham-extreme.db)៖

សូមចងចាំថាខ្ញុំបានឡើងលើក្តារហើយមានកាតគ្របដណ្តប់លើអ្វីៗទាំងអស់ចាប់ពីភាសាការជួបប្រជុំគ្នា និង សំនួរទាក់ទងនឹង Python រហូតដល់ការរៀនម៉ាស៊ីននិងស្ថិតិ។ វាជាវិធីច្រើនពេកសម្រាប់អ្វីដែលត្រូវការ។

**កំណត់ចំណាំនៅលើបណ្ណបង្ហាញ៖** ជាលើកដំបូងដែលអ្នកទទួលស្គាល់អ្នកដឹងពីចម្លើយ សូមកុំសម្គាល់វាថាត្រូវបានគេស្គាល់។ អ្នកត្រូវតែមើល
កាតដូចគ្នានិងឆ្លើយវាច្រើនដងឱ្យបានត្រឹមត្រូវមុនពេលដែលអ្នកពិតជាដឹង។ ពាក្យដដែលៗនឹងធ្វើឱ្យចំណេះដឹងនោះកាន់តែស៊ីជម្រៅ
ខួរក្បាលរបស់អ្នក។

ជំរើសមួយផ្សេងទៀតក្នុងការប្រើប្រាស់បណ្តាញកាតរបស់ខ្ញុំគឺ [Anki](http://ankisrs.net/) ដែលត្រូវបានណែនាំអោយខ្ញុំច្រើនដង។ វាប្រើប្រព័ន្ធពាក្យដដែលៗដើម្បីជួយអ្នកចងចាំ។
វាមានភាពងាយស្រួលសម្រាប់អ្នកប្រើដែលមាននៅលើគ្រប់វេទិកាទាំងអស់និងមានប្រព័ន្ធធ្វើសមកាលកម្មពពក។ វាមានតម្លៃ ២៥ ដុល្លារលើប្រព័ន្ធប្រតិបត្តិការ iOS ប៉ុន្តែមិនគិតថ្លៃនៅលើវេទិកាផ្សេងទៀតទេ។

មូលដ្ឋានទិន្នន័យបណ្ណបង្ហាញរបស់ខ្ញុំក្នុងទំរង់អាគី (Anki) ៖ https://ankiweb.net/shared/info/25173560 (សូមអរគុណ [@xiewenya](https://github.com/xiewenya)

### ៣. ចាប់ផ្តើមធ្វើសំណួរសម្ភាសន៍សរសេរកូដខណៈពេលដែលអ្នកកំពុងរៀនរចនាសម្ព័ន្ធទិន្នន័យ (Data Structure) និង ក្បួនដោះស្រាយ (Algorithm)

អ្នកត្រូវអនុវត្តអ្វីដែលអ្នកកំពុងរៀនដើម្បីដោះស្រាយបញ្ហាឬអ្នកនឹងភ្លេច។ ខ្ញុំបានធ្វើកំហុសនេះ។ នៅពេលដែលអ្នកបានរៀនប្រធានបទមួយ
ហើយមានអារម្មណ៍ស្រួលជាមួយវាដូចជាបញ្ជីភ្ជាប់បើកសៀវភៅសម្ភាសន៍កូដសរសេរមួយហើយធ្វើសំណួរពីរបីទាក់ទងនឹង
បញ្ជីដែលបានភ្ជាប់។ បន្ទាប់មកបន្តទៅប្រធានបទសិក្សាបន្ទាប់។ បន្ទាប់មកពេលក្រោយ ត្រលប់ក្រោយហើយធ្វើបញ្ហាបញ្ជីដែលបានភ្ជាប់ផ្សេងទៀត
ឬបញ្ហាការហៅឡើងវិញឬអ្វីផ្សេងទៀត។ ប៉ុន្តែនៅតែធ្វើបញ្ហានៅពេលអ្នកកំពុងរៀន។ អ្នកមិនត្រូវបានគេជួលដើម្បីចំណេះដឹងទេ
ប៉ុន្តែរបៀបដែលអ្នកអនុវត្តចំណេះដឹង។ មានសៀវភៅនិងគេហទំព័រជាច្រើនដែលខ្ញុំសូមណែនាំ។
សូមមើលនៅទីនេះសម្រាប់ព័ត៌មានបន្ថែម: [ការអនុវត្តសំណួរសំណួរសរសេរកូដ](#coding-question-practice)

### 4. ពិនិត្យឡើងវិញ ពិនិត្យឡើងវិញ ពិនិត្យឡើងវិញ

ខ្ញុំរក្សាទុកសន្លឹកបន្លំមួយសន្លឹកនៅលើ ASCII, OSI stack, សញ្ញាណសំគាល់ធំ ៗ (Big-O) និងច្រើនទៀត។ ខ្ញុំសិក្សាវានៅពេលខ្ញុំមានពេលទំនេរខ្លះ។

សម្រាកពីបញ្ហាសរសេរកម្មវិធីរយៈពេលកន្លះម៉ោង ហើយអានកាតរបស់អ្នក។

### 5. ផ្តោតអារម្មណ៍

មានការរំខានជាច្រើនដែលអាចចំណាយពេលដ៏មានតម្លៃ។ ការផ្តោតអារម្មណ៍គឺពិបាក។ បើកតន្ត្រីមួយចំនួនដែលគ្មានទំនុកច្រៀងទេអ្នកនឹងអាចផ្តោតអារម្មណ៍បានល្អ។

---

### What you won't see covered
## អ្វីដែលអ្នកនឹងមិនឃើញគ្របដណ្តប់

ទាំងនេះជាបច្ចេកវិទ្យាដែលមានជាទូទៅប៉ុន្តែមិនមែនជាផ្នែកនៃផែនការសិក្សានេះទេ៖

- SQL
- Javascript
- HTML, CSS និងបច្ចេកវិទ្យាផ្នែក front-end

---

### The Daily Plan
## ផែនការប្រចាំថ្ងៃ

មុខវិជ្ជាខ្លះចំណាយពេលមួយថ្ងៃហើយ មុខវិជ្ជាខ្លះនឹងចំណាយពេលច្រើនថ្ងៃ។ អ្នកខ្លះរៀនតែគ្មានអ្វីអនុវត្ត។

ជារៀងរាល់ថ្ងៃខ្ញុំយកប្រធានបទមួយចេញពីបញ្ជីខាងក្រោមមើលវីដេអូអំពីប្រធានបទនោះហើយសរសេរកូតនៅក្នុង៖
- C - ប្រើរចនាសម្ព័ន្ធ និង មុខងារដែលយករចនាសម្ព័ន្ធ * និង អ្វីផ្សេងទៀតជា Arguments។
- C++ - ដោយមិនប្រើមុខងារដែលភ្ជាប់មកជាមួយនឹង ភាសា
- C++ - ប្រើប្រភេទដែលមានស្រាប់ដូចជា STL's::list សម្រាប់បញ្ជីភ្ជាប់ (Linked list)
- Python - ប្រើប្រភេទដែលមានស្រាប់ (ដើម្បីរំលឹក Python)
- និងសរសេរការធ្វើតេស្តដើម្បីធានាថាខ្ញុំធ្វើវាបានត្រឹមត្រូវពេលខ្លះគ្រាន់តែប្រើសេចក្តីថ្លែងអះអាងសាមញ្ញ assert()
- អ្នកអាចធ្វើ Jav ឬ អ្វីផ្សេងទៀតនេះគ្រាន់តែជារឿងរបស់ខ្ញុំប៉ុណ្ណោះ។

អ្នកមិនត្រូវការរបស់ទាំងអស់នេះទេ។ អ្នកត្រូវការតែ [ភាសាមួយសម្រាប់ការសម្ភាសន៍](#pick-one-language-for-the-interview) ។

ហេតុអ្វីត្រូវកូដទាំងអស់នេះ?
- អនុវត្ត អនុវត្ត អនុវត្តរហូតដល់ខ្ញុំច្បាស់ហើយអាចធ្វើវាដោយគ្មានបញ្ហា (អ្នកខ្លះមានករណីកំរច្រើន និង ព័ត៌មានលំអិតនៃការរក្សាទុកសៀវភៅដើម្បីចងចាំ)
- ធ្វើការនៅក្នុងឧបសគ្គ (បែងចែក / លុបចេញអង្គចងចាំ (Memory) ដោយគ្មានជំនួយពីការប្រមូលសំរាម (Gabage Collection) (លើកលែងតែ Python ឬ Java))
- ប្រើប្រភេទដែលមានស្រាប់ដូច្នេះខ្ញុំមានបទពិសោធន៍ប្រើឧបករណ៍ដែលមានស្រាប់សម្រាប់ការប្រើប្រាស់ដូចពេលធ្វេីការ (មិនមែនថាសរសេរការអនុវត្តន៍បញ្ជី (Linked List) របស់ខ្ញុំផ្ទាល់ក្នុងពេលធ្វេីការ)

ខ្ញុំប្រហែលជាមិនមានពេលវេលាដើម្បីធ្វើការទាំងអស់សម្រាប់មុខវិជ្ជាទាំងអស់នោះទេប៉ុន្តែខ្ញុំនឹងព្យាយាម។

អ្នកអាចឃើញកូដរបស់ខ្ញុំនៅទីនេះ៖

- [C](https://github.com/jwasham/practice-c)
- [C++](https://github.com/jwasham/practice-cpp)
- [Python](https://github.com/jwasham/practice-python)

អ្នកមិនចាំបាច់ទន្ទេញចាំគ្រប់ក្បួនដោះស្រាយទាំងអស់។

សរសេរកូដនៅលើក្ដារខៀនឬក្រដាស មិនមែនកុំព្យូទ័រទេ។ សាកល្បងជាមួយធាតុចូលគំរូមួយចំនួន។ បន្ទាប់មកសាកល្បងវានៅលើកុំព្យូទ័រ។

## ចំណេះដឹងចាំបាច់

- [ ] **រៀន C**
    - C គឺនៅគ្រប់ទីកន្លែង។ អ្នកនឹងឃើញឧទាហរណ៍នៅក្នុងសៀវភៅការបង្រៀនវីដេអូ *នៅគ្រប់ទីកន្លែង* ពេលអ្នកកំពុងសិក្សា។
    
    - [ ] [ភាសាសរសេរកម្មវិធី C, ភាគ ២](https://www.amazon.com/Programming-Language-Brian-W-Kernighan/dp/0131103628)
        
        - នេះគឺជាសៀវភៅខ្លីមួយប៉ុន្តែវានឹងផ្តល់ឱ្យអ្នកនូវភាសា C យ៉ាងល្អហើយប្រសិនបើអ្នកអនុវត្តវាបន្តិច អ្នកនឹងឆាប់ស្ទាត់ជំនាញ។ ការយល់ដឹង C ជួយអ្នកឱ្យយល់ពីរបៀបដែលកម្មវិធីនិងការចងចាំដំណើរការ។
        
        - [ចម្លើយចំពោះសំណួរ](https://github.com/lekkas/c-algorithms)

- [ ] **របៀបដែលកុំព្យូទ័រដំណើរការកម្មវិធី:**
    - [ ] [តើស៊ីភីយូប្រតិបត្តិកម្មវិធីមួយយ៉ាងដូចម្តេច? (វីដេអូ)](https://www.youtube.com/watch?v=XM4lGflQFvA)
    - [ ] [របៀបគណនាកុំព្យូទ័រ - ALU (វីដេអូ)](https://youtu.be/1I5ZMmrOfnA)
    - [ ] [ចុះបញ្ជី (Registers) និង រ៉េម (RAM) (វីដេអូ)](https://youtu.be/fpnE6UAfbtU)
    - [ ] [អង្គភាពកែច្នៃកណ្តាល (ស៊ីភីយូ) (The Central Processing Unit) (វីដេអូ)](https://youtu.be/FZGugFqdr60)
    - [ ] [សេចក្តីណែនាំនិងកម្មវិធី (វីដេអូ)](https://youtu.be/zltgXvg6r3k)

---

### Algorithmic complexity / Big-O / Asymptotic analysis
## ភាពស្មុគស្មាញនៃក្បួនដោះស្រាយ / ការវិភាគ Big-O

- គ្មានអ្វីត្រូវអនុវត្តទេ
- មានវីដេអូជាច្រើននៅទីនេះ។ គ្រាន់តែមើលឱ្យបានគ្រប់គ្រាន់រហូតដល់អ្នកយល់។ អ្នកអាចត្រលប់មកពិនិត្យឡើងវិញជានិច្ច។
- ប្រសិនបើការបង្រៀនមួយចំនួនមានភាពស្រងូតស្រងាត់អ្នកអាចរំលងដល់ក្រោមហើយមើលវីដេអូគណិតវិទ្យាដែលដាច់ពីគ្នាដើម្បីទទួលបានចំណេះដឹងជាមូលដ្ឋាន។
- [ ] [Harvard CS50 - Asymptotic Notation (វីដេអូ)](https://www.youtube.com/watch?v=iOq5kSKqeR4)
- [ ] [កំណត់ចំណាំ Big-O (ការបង្រៀនរហ័សទូទៅ) (វីដេអូ)](https://www.youtube.com/watch?v=V6mKVRU1evU)
- [ ] [Big O Notation (និង Omega និង Theta) - ការពន្យល់គណិតវិទ្យាល្អបំផុត (វីដេអូ)](https://www.youtube.com/watch?v=ei-A_wy5Yxw&index=2&list=PL1BaGV1cIH4UhkL8a9bJGG356covJ76qN)
- [ ] Skiena៖
    - [វីដេអូ](https://www.youtube.com/watch?v=gSyDMtdPNpU&index=2&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b)
    - [ស្លាយ](http://www3.cs.stonybrook.edu/~algorith/video-lectures/2007/lecture2.pdf)
- [ ] [ការណែនាំមួយចំពោះការវិភាគស្មុគស្មាញនៃគណិតវិទ្យា](http://discrete.gr/complexity/)
- [ ] [លំដាប់នៃការលូតលាស់ (វីដេអូ)](https://www.coursera.org/lecture/algorithmic-thinking-1/orders-of-growth-6PKkX)
- [ ] [ការវិភាគអាមីស្តូតូទិក (Amortized) (វីដេអូ)](https://www.coursera.org/lecture/algorithmic-thinking-1/asymptotics-bXAtM)
- [ ] [UC Berkeley Big O (មានវីដេអូ)](https://archive.org/details/ucberkeley_webcast_VIS4YDpuP98)
- [ ] [UC Berkeley Big Omega (វីដេអូ)](https://archive.org/details/ucberkeley_webcast_ca3e7UVmeUc)
- [ ] [ការវិភាគរំលោះ (Amortized) (វីដេអូ)](https://www.youtube.com/watch?v=B3SpQZaAZP4&index=10&list=PL1BaGV1cIH4UhkL8a9bJGG356covJ76qN)
- [ ] [បង្ហាញរូបភាព "Big-O" (វីដេអូ)](https://www.coursera.org/lecture/alacticmic-thinking-1/illustrating-big-o-YVqzv)
- [ ] TopCoder (រួមបញ្ចូលទាំងទំនាក់ទំនងកើតឡើងវិញនិងទ្រឹស្តីបទមេ)៖
    - [ភាពស្មុគស្មាញនៃការគណនា៖ ផ្នែកទី ១](https://www.topcoder.com/community/competitive-programming/tutorials/computational-complexity-section-1/)
    - [ភាពស្មុគស្មាញនៃការគណនា៖ ផ្នែកទី ២](https://www.topcoder.com/community/competitive-programming/tutorials/computational-complexity-section-2/)
- [ ] [សន្លឹកជំនួយ](http://bigocheatsheet.com/)

---

### Data Structures
## រចនាសម្ព័ន្ធទិន្នន័យ

- ### Arrays
    - អនុវត្តវ៉ិចទ័រប្តូរទំហំដោយស្វ័យប្រវត្តិ។
    - [ ] ការពិពណ៌នា៖
        - [Arrays (វីដេអូ)](https://www.coursera.org/learn/data-structures/lecture/OsBSF/arrays)
        -[UC Berkeley CS61B - អារេ លីនែអ៊ែរ និង ពហុវិមាត្រ (វីដេអូ)](https://archive.org/details/ucberkeley_webcast_Wp8oiO_CZZE) (ចាប់ផ្តើមមើលចាប់ពី ១៥នាទី ៣២វិនាទី)
        - [Arrays មូលដ្ឋាន (វីដេអូ)](https://archive.org/details/0102WhatYouShouldKnow/02_04-basicArrays.mp4)
        - [ពហុវិមាត្រ (វីដេអូ)](https://archive.org/details/0102WhatYouShouldKnow/02_05-multidimensionalArrays.mp4)
        - [Arrays ឌីណាមិចេ (វីដេអូ)](https://www.coursera.org/learn/data-structures/lecture/EwbnV/dynamic-arrays)
        - [Jagged Arrays (វីដេអូ)](https://www.youtube.com/watch?v=1jtrQqYpt7g)
        - [Jagged Arrays (វីដេអូ)](https://archive.org/details/0102WhatYouShouldKnow/02_06-jaggedArrays.mp4)
        - [ការប្តូរទំហំ Arrays (វីដេអូ)](https://archive.org/details/0102WhatYouShouldKnow/03_01-resizableArrays.mp4)
    - [ ] អនុវត្តវ៉ិចទ័រ (បំលែង Arrays ដោយប្តូរទំហំស្វ័យប្រវត្តិ)៖
        - [ ] អនុវត្តការសរសេរកូដដោយប្រើArrays និង ទ្រនិចចង្អុល និង គណិតទ្រនិចដើម្បីលោតទៅសន្ទស្សន៍មួយ។
        - [ ] Arrays ទិន្នន័យថ្មីដែលមានអង្គចងចាំបម្រុងទុក
            - អាចបែងចែកArraysនៅក្រោមក្រណាត់ដោយគ្រាន់តែមិនប្រើលក្ខណៈពិសេសរបស់វា
            - ចាប់ផ្តើមជាមួយលេខ ១៦ ឬបើលេខចាប់ផ្តើមធំជាងប្រើថាមពល ២ - ១៦, ៣២, ៦៤, ១២៨
        - [ ] size() - ចំនួនធាតុ
        - [ ] capacity() - ចំនួនធាតុដែលវាអាចផ្ទុកបាន
        - [ ] is_empty()
        - [ ] at(index) - ត្រឡប់ធាតុនៅទីតាំងដែលបានផ្តល់ឱ្យ បេីទីតាំងនៅក្រៅព្រំដែន វានឹង មានកុំហស
        - [ ] push(item)
        - [ ] insert(index, item) - បញ្ចូលធាតុនៅទីតាំង ប្តូរតម្លៃទីតាំង និងធាតុនៅខាងក្រោមទៅខាងស្តាំ
        - [ ] prepend (item) - អាចប្រើបញ្ចូលខាងលើនៅទីតាំង ០
        - [ ] pop() - ដកចេញពីចុងបញ្ចប់តម្លៃត្រឡប់មកវិញ
        - [ ] delete(index) - លុបធាតុនៅទីតាំងដែលអោយ ផ្លាស់ប្តូរធាតុនៅពីក្រោយទាំងអស់
        - [ ] remove(item) - រកមើលតម្លៃនិងយកទីតាំងចេញដែលផ្ទុកវាចេញ (ទោះបីជានៅកន្លែងច្រើនក៏ដោយ)
        - [ ] find(item) - រកមើលតម្លៃហើយត្រឡប់វិញនៅទីតាំងដំបូងជាមួយតម្លៃនោះ បើរកមិនឃើញត្រលប់វិញ -1
        - [ ] resize(new_capacity) // មុខងារឯកជន
            - ពេលទំហំ Array ដល់កំណត់, ផ្លាស់ប្តូរទំហំទ្វេដងទំហំ
            - នៅពេលដែលចាប់យកវត្ថុមួយ ប្រសិនបើទំហំគឺ 1/4 នៃទំហំសរុប, ផ្លាស់ប្តូរទំហំដល់ពាក់កណ្តាល
    - [ ] ពេលវេលា
        - O(១) ត្រូវបន្ថែម / ដកចេញនៅចុងបញ្ចប់ (សងវិញសម្រាប់ការបែងចែកសម្រាប់ទំហំបន្ថែម) ទីតាំង
        - O(n) ដើម្បីបញ្ចូល / ដកចេញនៅកន្លែងផ្សេងទៀត
    - [ ] លំហ
        - ជាប់ទាក់ទងនឹងការចងចាំដូច្នេះភាពជិតស្និទ្ធជួយដល់ការអនុវត្ត
        - ទំហំត្រូវការ = (ទំហំ Array, ដែល >= n) * ទំហំនៃធាតុ, ប៉ុន្តែបើទោះបីជា 2n, នៅតែ O (n)

---

- ### Linked Lists
    - [ ] ការពិពណ៌នា៖
        - [ ] [Singly Linked Lists (វីដេអូ)](https://www.coursera.org/learn/data-structures/lecture/kHhgK/singly-linked-lists)
        - [ ] [CS 61B - Linked Lists ១ (វីដេអូ)](https://archive.org/details/ucberkeley_webcast_htzJdKoEmO0)
        - [ ] [CS 61B - Linked Lists ២ (វីដេអូ)](https://archive.org/details/ucberkeley_webcast_-c4I3gFYe3w)
    - [ ] [កូដ C (វីដេអូ)](https://www.youtube.com/watch?v=QN6FPiD0Gzo)
        - មិនមែនវីដេអូទាំងមូលទេគឺគ្រាន់តែជាផ្នែកអំពីរចនាសម្ព័ន្ធ (Data Structure) និងការបែងចែក Memory ។
    - [ ] Linked List vs Arrays:
        - [Core Linked Lists Vs Arrays (វីដេអូ)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/rjBs9/core-linked-lists-vs-arrays)
        - [នៅក្នុងពិភពពិត Linked Lists Vs Arrays (វីដេអូ)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/QUaUd/in-the-real-world-lists-vs-arrays)
    - [ ] [ហេតុអ្វីអ្នកគួរចៀសវាង linked lists (វីដេអូ)](https://www.youtube.com/watch?v=YQs6IC-vgmo)
    - [ ] Gotcha: you need pointer to pointer knowledge:
        (សម្រាប់ពេលអ្នកហុច pointer ទៅមុខងារមួយដែលអាចផ្លាស់ប្តូរអាស័យដ្ឋានដែលព្រួញចង្អុល)
        ទំព័រនេះគ្រាន់តែដើម្បីស្វែងយល់ពី pointer ទៅ pointer ។ ខ្ញុំមិនណែនាំបញ្ជីឈ្មោះបែបត្រាប់តាមនេះទេ។ ភាពងាយស្រួលក្នុងការអាននិងរក្សាបាននូវភាពលំបាកដោយសារតែភាពឆ្លាតវៃ។
        - [Pointer ទៅ pointer](https://www.eskimo.com/~scs/cclass/int/sx8.html)
    - [ ] អនុវត្ត (ខ្ញុំបានធ្វើដោយប្រើទ្រនិចកន្ទុយនិងដោយគ្មាន)៖
        - [ ] size() - ត្រឡប់ចំនួនធាតុទិន្នន័យក្នុងបញ្ជី
        - [ ] empty() - bool ត្រឡប់ពិតបើទទេ
        - [ ] value_at(index) - ត្រឡប់តម្លៃនៃធាតុទី (ចាប់ផ្តើមពីលេខ ០ ដំបូង)
        - [ ] push_front(តម្លៃ) - បន្ថែមធាតុនៅខាងមុខបញ្ជី
        - [ ] pop_front() - យកធាតុខាងមុខចេញហើយប្រគល់តម្លៃរបស់វាមកវិញ
        - [ ] push_back(តម្លៃ) - បន្ថែមធាតុនៅចុងបញ្ចប់
        - [ ] pop_back() - យកធាតុបញ្ចប់ហើយត្រឡប់តម្លៃរបស់វា
        - [ ] front() - ទទួលបានតម្លៃនៃធាតុខាងមុខ
        - [ ] back() - ទទួលបានតម្លៃនៃធាតុបញ្ចប់
        - [ ] insert(index, តម្លៃ) - បញ្ចូលតម្លៃនៅindex ដូច្នេះធាតុបច្ចុប្បន្ននៅindexនោះត្រូវបានចង្អុលទៅធាតុថ្មីនៅindex។
        - [ ] erase(index) - យក Node ចេញនៅ index ដែលបានផ្តល់ឱ្យ
        - [ ] value_n_from_end(n) - ត្រឡប់តម្លៃ Node ទីពីខាងចុងបញ្ជី
        - [ ] reverse() - បញ្ច្រាស់បញ្ជី
        - [ ] remove_value(តម្លៃ) - លុបធាតុដំបូងក្នុងបញ្ជីជាមួយតម្លៃនេះ
    - [ ] Doubly-linked List
        - [ការពិពណ៌នា (វីដេអូ)](https://www.coursera.org/learn/data-structures/lecture/jpGKD/doubly-linked-lists)
        - មិនចាំបាច់អនុវត្តទេ

---

- ### Stack
    - [ ] [Stack (វីដេអូ)](https://www.coursera.org/learn/data-structures/lecture/UdKzQ/stacks)
    - [ ] [ការប្រើ Stack ចូលមុនចេញក្រោយ (វីដេអូ)](https://archive.org/details/0102WhatYouShouldKnow/05_01-usingStacksForLast-inFirst-out.mp4)
    - [ ] នឹងមិនអនុវត្តទេ។ ការអនុវត្តជាមួយ Array គឺមិនសំខាន់។

- ### Queue
    - [ ] [ការប្រើ Queue ចូលមុនចេញមុន(វីដេអូ)](https://archive.org/details/0102WhatYouShouldKnow/05_03-usingQueuesForFirst-inFirst-out.mp4)
    - [ ] [Queue (វីដេអូ)](https://www.coursera.org/lecture/data-structures/queues-EShpq)
    - [ ] [Circular buffer/FIFO](https://en.wikipedia.org/wiki/Circular_buffer)
    - [ ] [Queue អាទិភាព (វីដេអូ)](https://archive.org/details/0102WhatYouShouldKnow/05_04-priorityQueuesAndDeques.mp4)
    - [ ] ប្រើ linked-list ដែលមានភ្ជាប់ជាមួយទ្រនិចនៅកន្ទុយ៖
        - enqueue(តម្លៃ) - បន្ថែមតម្លៃនៅទីតាំងនៅកន្ទុយ
        - dequeue() - ត្រឡប់តម្លៃនិងយកធាតុដែលបានបន្ថែមថ្មីៗចេញ (ផ្នែកខាងមុខ)
        - empty()
    - [ ] អនុវត្តដោយប្រើអារេ Array ទំហំថេរ៖
        - enqueue(តម្លៃ) - បន្ថែមធាតុនៅចុងបញ្ចប់នៃការផ្ទុកដែលមាន
        - dequeue() - ត្រឡប់តម្លៃនិងយកធាតុដែលបានបន្ថែមថ្មីៗចេញ
        - empty()
        - full()
    - [ ] ថ្លៃ៖
        - ការអនុវត្តមិនល្អដោយប្រើlinked listដែលអ្នករៀបជាជួរនៅនឹងក្បាលនិងដេស្កាយនៅកន្ទុយប្រហែលជា O(n)
            ដោយសារតែអ្នកត្រូវការនៅជាប់នឹងធាតុចុងក្រោយ, បណ្តាលឱ្យ dequeue គ្នាឆ្លងកាត់ពេញលេញ
        - enqueue: O(1) (amortized, linked list and array [probing])
        - dequeue: O(1) (linked list and array)
        - empty: O(1) (linked list and array)

- ### តារាងហាស (Hash table)
    - [ ] វីដេអូ៖
        - [ ] [Hashing with Chaining (វីដេអូ)](https://www.youtube.com/watch?v=0M_kIqwbFo&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=8)
        - [ ] [Table Doubling, Karp-Rabin (វីដេអូ)](https://www.youtube.com/watch?v=BRO7mVIFt08&index=9&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb)
        - [ ] [Open Addressing, Cryptographic Hashing (វីដេអូ)](https://www.youtube.com/watch?v=rvdJDijO2Ro&index=10&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb)
        - [ ] [PyCon 2010: វចនានុក្រមដ៏អស្ចារ្យ (វីដេអូ)](https://www.youtube.com/watch?v=C4Kc8xzcA68)
        - [ ] [(កម្រិតខ្ពស់) Randomization: Universal & Perfect Hashing (វីដេអូ)](https://www.youtube.com/watch?v=z0lJ2k0sl1g&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=11)
        - [ ] [(ជឿនលឿន) Perfect hashing (វីដេអូ)](https://www.youtube.com/watch?v=N0COwN14gt0&list=PL2B4EEwhKD-NbwZ4ezj7gyc_3yNrojKM9&index=4)

    - [ ] វគ្គសិក្សាអនឡាញ៖
        - [ ] [ស្វែងយល់អំពីមុខងារ Hash (វីដេអូ)](https://archive.org/details/0102WhatYouShouldKnow/06_02-understandingHashFunctions.mp4)
        - [ ] [ការប្រើតារាងHash (វីដេអូ)](https://archive.org/details/0102WhatYouShouldKnow/06_03-usingHashTables.mp4)
        - [ ] [គាំទ្រ Hash (វីដេអូ)](https://archive.org/details/0102WhatYouShouldKnow/06_04- ឧបត្ថម្ភគាំទ្រហាន់ឌ្រី)
        - [ ] [តារាងជំនួយភាសា Hash(វីដេអូ)](https://archive.org/details/0102WhatYouShouldKnow/06_05-languageSupportForHashTables.mp4)
        - [ ] [Core Hash Tables (វីដេអូ)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/m7UuP/core-hash-tables)
        - [ ] [រចនាសម្ព័ន្ធទិន្នន័យ (វីដេអូ)](https://www.coursera.org/learn/data-structures/home/week/4)
        - [ ] [បញ្ហាសៀវភៅទូរស័ព្ទ (វីដេអូ)](https://www.coursera.org/learn/data-structures/lecture/NYZZP/phone-book-problem)
        - [តារាងចែកចាយ]
            - [ការផ្ទុកឡើងភ្លាមៗនិងការបង្កើនប្រសិទ្ធភាពផ្ទុកនៅក្នុងប្រអប់ឯកសារ (វីដេអូ)](https://www.coursera.org/learn/data-structures/lecture/DvaIb/instant-uploads-and-storage-optimization-in-dropbox)
            - [តារាងហាសចែកចាយ (វីដេអូ)](https://www.coursera.org/learn/data-structures/lecture/tvH8H/distributed-hash-tables)

    - [ ] អនុវត្តជាមួយអារេដោយប្រើការស៊ើបអង្កេតលីនេអ៊ែរ
        - hash(k, m) - m គឺជាទំហំនៃតារាង hash
        - add(key, value) - ប្រសិនបើមានកូនសោររួចហើយ, ធ្វើបច្ចុប្បន្នភាពតម្លៃ
        - exists(key)
        - get(key)
        - remove(key)

---

### More Knowledge
## ចំណេះដឹងបន្ថែម

- ### Binary search
    - [ ] [Binary search (វីដេអូ)](https://www.youtube.com/watch?v=D5SrAga1pno)
    - [ ] [Binary search (វីដេអូ)](https://www.khanacademy.org/computing/computer-science/algorithms/binary-search/a/binary-search)
    - [ ] [លម្អិត](https://www.topcoder.com/community/competitive-programming/tutorials/binary-search/)
    - [ ] អនុវត្ត៖
        - Binary search (នៅលើជួរអារេនៃចំនួនគត់)
        - Binary search ដោយប្រើការហៅខ្លួនឯង

- ### ប្រតិបតិ្តការ Bitwise
    - [ ] [សន្លឹកជំនួយ Bits](https://github.com/jwasham/coding-interview-university/blob/master/extras/cheat%20sheets/bits-cheat-sheet.pdf) 
        - អ្នកគួរតែស្គាល់ អំណាច ២ ពី (២ ^ ១ ដល់ ២ ^ ១៦ និង ២ ^ ៣២)
    - [ ] ទទួលបានការយល់ដឹងដ៏ល្អអំពីការរៀបចំBitsជាមួយ៖ &, |, ^, ~, >>, <<
        - [ ] [ពាក្យ](https://en.wikipedia.org/wiki/Word_ (computer_architecture))
        - [ ] ការណែនាំល្អ៖
            ការធ្វើចលនាBits (វីដេអូ)](https://www.youtube.com/watch?v=7jkIUgLC29I)
        - [ ] [C ការបង្រៀនសរសេរកម្មវិធី ២-១០: ប្រតិបត្តិការ Bitwise (វីដេអូ)](https://www.youtube.com/watch?v=d0AwjSpNXR0)
        - [ ] [ការរៀបចំBits](https://en.wikipedia.org/wiki/Bit_manipulation)
        - [ ] [ប្រតិបតិ្តការ Bitwise](https://en.wikipedia.org/wiki/Bitwise_operation)
        - [ ] [Bithacks](https://graphics.stanford.edu/~seander/bithacks.html)
        - [ ] [The Bit Twiddler](https://bits.stephan-brumme.com/)
        - [ ] [The Bit Twiddler Interactive](https://bits.stephan-brumme.com/interactive.html)
        - [ ] [Bit Hacks (វីដេអូ)](https://www.youtube.com/watch?v=ZusiKXcz_ac)
    - [ ] 2s និង 1s បំពេញបន្ថែម
        - [Binary: Plusses & Minuses (ហេតុអ្វីយើងប្រើសមពីរ) (វីដេអូ)](https://www.youtube.com/watch?v=lKTsv6iVxV4)
        - [១s បំពេញ](https://en.wikipedia.org/wiki/Ones%27_complement)
        - [២ វិនាទីបំពេញ](https://en.wikipedia.org/wiki/Two%27s_complement)
    - [ ] រាប់សំណុំ bits
        - [វិធី ៤ យ៉ាងដើម្បីរាប់ប៊ីតជាសាមសិបប៊ីត (វីដេអូ)](https://youtu.be/Hzuzo9NJrlc)
        - [រាប់ប៊ីត](https://graphics.stanford.edu/~seander/bithacks.html#CountBitsSetKernighan)
        - [របៀបរាប់ចំនួនសំណុំប៊ីតក្នុងចំនួនគត់ ៣២ ប៊ីត](http://stackoverflow.com/questions/109023/how-to-count-the-number-of-set-bits-in-a-32-bit- ចំនួនគត់)
    - [ ] ប្តូរតម្លៃ
        - [ប្តូរ](https://bits.stephan-brumme.com/swap.html)
    - [ ] តម្លៃដាច់ខាត:
        - [អាំងតេក្រាលពេញលេញ](https://bits.stephan-brumme.com/absInteger.html)

---

## Trees

- ### Trees - កំណត់ត្រា និង ព័ត៌មាន
    - [ ] [ស៊េរី៖ ចំនុចសំខាន់ Trees (វីដេអូ)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/ovovP/core-trees)
    - [ ] [ស៊េរី៖ Trees (វីដេអូ)](https://www.coursera.org/learn/data-structures/lecture/95qda/trees)
    - ការសាងសង់ tree
    - ការឆ្លងកាត់ tree
    - ក្បួនដោះស្រាយ
    - [ ] [BFS(breadth-first search) និង DFS(depth-first search) (វីដេអូ)](https://www.youtube.com/watch?v=uWL6FJhq5fM)
        - កំណត់សំគាល់របស់ BFS:
           - level order (BFS, ដោយប្រេី queue)
           - ភាពស្មុគស្មាញពេលវេលា: O(n)
           - ភាពស្មុគស្មាញនៃលំហ: ល្អបំផុត៖ O(1), អាក្រក់បំផុត៖ O(n/2)=O(n)
        - DFS notes:
            - ភាពស្មុគស្មាញពេលវេលា: O(n)
            - ភាពស្មុគស្មាញនៃលំហ:
                ល្អបំផុត៖ O(log n) - មធ្យមកម្ពស់ tree
                អាក្រក់បំផុត៖ O(n)
            - inorder (DFS: ឆ្វេង, ខ្លួនឯង, ស្តាំ)
            - postorder (DFS: ឆ្វេង, ស្តាំ, ខ្លួនឯង)
            - preorder (DFS: self, left, right)
 
- ### Binary search trees: BSTs
    - [ ] [ការពិនិត្យឡើងវិញ Binary Search Tree (វីដេអូ)](https://www.youtube.com/watch?v=x6At0nzX92o&index=1&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6)
    - [ ] [ស៊េរី (វីដេអូ)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/p82sw/core-introduction-to-binary-search-trees)
        - ចាប់ផ្តើមជាមួយតារាងនិមិត្តសញ្ញាហើយឆ្លងកាត់ការអនុវត្ត BST
    - [ ] [សេចក្តីផ្តើម (វីដេអូ)](https://www.coursera.org/learn/data-structures/lecture/E7cXP/introduction)
    - [ ] [MIT (វីដេអូ)](https://www.youtube.com/watch?v=9Jry5-82I68)
    - C/C++:
        - [ ] [Binary search tree - ការអនុវត្តក្នុង C/C++ (វីដេអូ)](https://www.youtube.com/watch?v=COZK7NATh4k&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=28)
        - [ ] [BST ការអនុវត្តក្នុង - ការបែងចែក memory ក្នុង stack និង heap (វីដេអូ)](https://www.youtube.com/watch?v=hWokyBoo0aI&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=29)
        - [ ] [ស្វែងរកធាតុតូចបំផុត និង ធំបំផុតនៅក្នុង binary search tree (វីដេអូ)](https://www.youtube.com/watch?v=Ut90klNN264&index=30&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P)
        - [ ] [រកកំពស់ binary tree (វីដេអូ)](https://www.youtube.com/watch?v=_pnqMz5nrRs&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=31)
        - [ ] [Binary tree traversal - យុទ្ធសាស្ត្រ breadth-first និង depth-first (វីដេអូ)](https://www.youtube.com/watch?v=9RHO6jU--GU&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=32)
        - [ ] [Binary tree: Level Order Traversal (វីដេអូ)](https://www.youtube.com/watch?v=86g8jAQug04&index=33&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P)
        - [ ] [Binary tree traversal: Preorder, Inorder, Postorder (វីដេអូ)](https://www.youtube.com/watch?v=gm8DUJJhmY4&index=34&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P)
        - [ ] [ពិនិត្យមើលថាតើ binary tree គឺ binary search tree រឺទេ (វីដេអូ)](https://www.youtube.com/watch?v=yEwSGhSsT0U&index=35&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P)
        - [ ] [លុបធាតុពី Binary Search Tree (វីដេអូ)](https://www.youtube.com/watch?v=gcULXE7ViZw&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=36)
        - [ ] [Inorder Successor ក្នុង binary search tree មួយ (video)](https://www.youtube.com/watch?v=5cPbNCrdotA&index=37&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P)
    - [ ] ការអនុវត្ត:
        - [ ] insert    // ដាក់ធាតុក្នុង tree
        - [ ] get_node_count // ទទួលចំនួនធាតុដែលផ្ទុក
        - [ ] print_values // បង្ហាញតម្លៃក្នុង tree, ពី តូច ទៅ ធំ
        - [ ] delete_tree
        - [ ] is_in_tree // ត្រឡប់វិញ ពិត ប្រសិនបេីតម្លៃក្នុង tree
        - [ ] get_height // ត្រឡប់វិញ កំពស់ក្នុង nodes (កំពស់ single node គឺ 1)
        - [ ] get_min   // ត្រឡប់វិញ ធាតុតូចជាងគេ
        - [ ] get_max   // ត្រឡប់វិញ ធាតុធំជាងគេ
        - [ ] is_binary_search_tree
        - [ ] delete_value
        - [ ] get_successor // ត្រឡប់តម្លៃខ្ពស់បំផុតបន្ទាប់នៅក្នុងtreeបន្ទាប់ពីតម្លៃដែលបានផ្ដល់ ៕ បើគ្មានត្រឡប់ -1
        
- ### Heap / Priority Queue / Binary Heap
    - visualized as a tree, but is usually linear in storage (array, linked list)
    - [ ] [Heap](https://en.wikipedia.org/wiki/Heap_(data_structure))
    - [ ] [សេចក្តីផ្តើម (វីដេអូ)](https://www.coursera.org/learn/data-structures/lecture/2OpTs/introduction)
    - [ ] [ការអនុវត្តដំបូង (វីដេអូ)](https://www.coursera.org/learn/data-structures/lecture/z3l9N/naive-implementations)
    - [ ] [Binary Trees (វីដេអូ)](https://www.coursera.org/learn/data-structures/lecture/GRV2q/binary-trees)
    - [ ] [កំពស់ Tree (វីដេអូ)](https://www.coursera.org/learn/data-structures/supplement/S5xxz/tree-height-remark)
    - [ ] [ប្រតិបត្តិការមូលដ្ឋាន (វីដេអូ)](https://www.coursera.org/learn/data-structures/lecture/0g1dl/basic-operations)
    - [ ] [Binary Trees ពេញលេញ (វីដេអូ)](https://www.coursera.org/learn/data-structures/lecture/gl5Ni/complete-binary-trees)
    - [ ] [Pseudocode (វីដេអូ)](https://www.coursera.org/learn/data-structures/lecture/HxQo9/pseudocode)
    - [ ] [Heap Sort - លោតដើម្បីចាប់ផ្ដើម (វីដេអូ)](https://youtu.be/odNJmw5TOEE?list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&t=3291)
    - [ ] [Heap Sort (វីដេអូ)](https://www.coursera.org/learn/data-structures/lecture/hSzMO/heap-sort)
    - [ ] [ការកសាង heap (វីដេអូ)](https://www.coursera.org/learn/data-structures/lecture/dwrOS/building-a-heap)
    - [ ] [MIT: Heaps និង Heap Sort (វីដេអូ)](https://www.youtube.com/watch?v=B7hVxCmfPtM&index=4&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb)
    - [ ] [CS 61B មេរៀន 24: Priority Queues (វីដេអូ)](https://archive.org/details/ucberkeley_webcast_yIUFT6AKBGE)
    - [ ] [Linear Time BuildHeap (max-heap)](https://www.youtube.com/watch?v=MiyLo8adrWw)
    - [ ] ការអនុវត្ត max-heap:
        - [ ] insert
        - [ ] sift_up - ត្រូវការសំរាប់បញ្ចូល
        - [ ] get_max - ត្រឡប់ធាតុអតិបរិមាដោយមិនយកវាចេញ
        - [ ] get_size() - ត្រឡប់ចំនួននៃធាតុដែលបានរក្សាទុក
        - [ ] is_empty() - ត្រឡប់ពិតប្រសិនបើ heap មិនមានធាតុ
        - [ ] extract_max - ត្រឡប់ធាតុអតិបរិមាយកវាចេញ
        - [ ] sift_down - ត្រូវការសំរាប់ extract_max
        - [ ] remove(i) - យកធាតុចេញនៅ index x
        - [ ] heapify - បង្កើតheap ពីធាតុជាច្រើនដែលត្រូវការសម្រាប់ heap_sort
        - [ ] heap_sort() - យកarray ដែលមិនបានតម្រៀបហើយប្រែក្លាយវាទៅជាកន្លែងដែលបានតម្រៀបតាមកន្លែងដោយប្រើheapអតិបរមា។ t
            - ចំណាំ៖ ការប្រើ heap តូច ជំនួសនឹងជួយសន្សំប្រតិបត្តិការ ប៉ុន្តែត្រូវការទំហំទ្វេដង (មិនអាចធ្វើនៅនឹងកន្លែង) ។

---

## Sorting

- [ ] កំណត់សំគាល់:
    - អនុវត្ត sorts និងដឹងពីករណីដែលល្អ និង ដែលអាក្រក់, ភាពស្មុគស្មាញជាមធ្យមនីមួយៗ:
        - កុំប្រេី bubble sort - វាមិនល្អ - O(n^2), លុះត្រាតែ n <= 16
    - [ ] ស្ថេរភាពក្នុងក្បួនដោះស្រាយ sorting ("តើ Quicksort មានស្ថេរភាពឬ?")
        - [ស្ថេរភាពក្នុងក្បួនដោះស្រាយ Sorting](https://en.wikipedia.org/wiki/Sorting_algorithm#Stability)
        - [ស្ថេរភាពក្នុងក្បួនដោះស្រាយ Sorting](http://stackoverflow.com/questions/1517793/stability-in-sorting-algorithms)
        - [ស្ថេរភាពក្នុងក្បួនដោះស្រាយ Sorting](http://www.geeksforgeeks.org/stability-in-sorting-algorithms/)
        - [ស្ថេរភាពក្នុងក្បួនដោះស្រាយ Sorting](http://homepages.math.uic.edu/~leon/cs-mcs401-s08/handouts/stability.pdf)
    - [ ] តើក្បួនដោះស្រាយអ្វីខ្លះអាចត្រូវបានប្រើ linked lists? អាចត្រូវបានប្រើ arrays? អាចត្រូវបានប្រើទាំងពីរ?
        - ខ្ញុំនឹងមិនណែនាំឱ្យ Sort ជាមួយ linked list ប៉ុន្តែអាចប្រេី Merge Sort។
        - [Merge Sort សំរាប់ Linked List](http://www.geeksforgeeks.org/merge-sort-for-linked-list/)

- សំរាប់ heapsort, សូមមេីល Heap data structure ខាងលេី. Heap sort គឺល្អ, ប៉ុន្តែមិនមានស្ថេរភាពទេ.

- [ ] [Sedgewick - Mergesort (5 វីដេអូ)](https://www.coursera.org/learn/algorithms-part1/home/week/3)
    - [ ] [1. Mergesort](https://www.coursera.org/learn/algorithms-part1/lecture/ARWDq/mergesort)
    - [ ] [2. Bottom up Mergesort](https://www.coursera.org/learn/algorithms-part1/lecture/PWNEl/bottom-up-mergesort)
    - [ ] [3. ភាពស្មុគស្មាញ Sorting](https://www.coursera.org/learn/algorithms-part1/lecture/xAltF/sorting-complexity)
    - [ ] [4. ប្រៀបធៀប](https://www.coursera.org/learn/algorithms-part1/lecture/9FYhS/comparators)
    - [ ] [5. ស្ថេរភាព](https://www.coursera.org/learn/algorithms-part1/lecture/pvvLZ/stability)

- [ ] [Sedgewick - Quicksort (4 វីដេអូរ)](https://www.coursera.org/learn/algorithms-part1/home/week/3)
    - [ ] [1. Quicksort](https://www.coursera.org/learn/algorithms-part1/lecture/vjvnC/quicksort)
    - [ ] [2. Selection](https://www.coursera.org/learn/algorithms-part1/lecture/UQxFT/selection)
    - [ ] [3. Keys ស្ទួន](https://www.coursera.org/learn/algorithms-part1/lecture/XvjPd/duplicate-keys)
    - [ ] [4. Sorts ជាប្រព័ន្ធ](https://www.coursera.org/learn/algorithms-part1/lecture/QBNZ7/system-sorts)

- [ ] UC Berkeley:
    - [ ] [CS 61B មេរៀនទី 29: Sorting I (វីដេអូរ)](https://archive.org/details/ucberkeley_webcast_EiUvYS2DT6I)
    - [ ] [CS 61B មេរៀនទី 30: Sorting II (វីដេអូរ)](https://archive.org/details/ucberkeley_webcast_2hTY3t80Qsk)
    - [ ] [CS 61B មេរៀនទី 32: Sorting III (វីដេអូរ)](https://archive.org/details/ucberkeley_webcast_Y6LOLpxg6Dc)
    - [ ] [CS 61B មេរៀនទី 33: Sorting V (វីដេអូរ)](https://archive.org/details/ucberkeley_webcast_qNMQ4ly43p4)

- [ ] [Bubble Sort (វីដេអូរ)](https://www.youtube.com/watch?v=P00xJgWzz2c&index=1&list=PL89B61F78B552C1AB)
- [ ] [វិភាគ Bubble Sort (វីដេអូរ)](https://www.youtube.com/watch?v=ni_zk257Nqo&index=7&list=PL89B61F78B552C1AB)
- [ ] [Insertion Sort, Merge Sort (វីដេអូរ)](https://www.youtube.com/watch?v=Kg4bqzAqRBM&index=3&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb)
- [ ] [Insertion Sort (វីដេអូរ)](https://www.youtube.com/watch?v=c4BRHC7kTaQ&index=2&list=PL89B61F78B552C1AB)
- [ ] [Merge Sort (វីដេអូរ)](https://www.youtube.com/watch?v=GCae1WNvnZM&index=3&list=PL89B61F78B552C1AB)
- [ ] [Quicksort (វីដេអូរ)](https://www.youtube.com/watch?v=y_G9BkAm6B8&index=4&list=PL89B61F78B552C1AB)
- [ ] [Selection Sort (វីដេអូរ)](https://www.youtube.com/watch?v=6nDMgr0-Yyo&index=8&list=PL89B61F78B552C1AB)

- [ ] កូដ Merge sort:
    - [ ] [ការប្រើប្រាស់ output array (C)](http://www.cs.yale.edu/homes/aspnes/classes/223/examples/sorting/mergesort.c)
    - [ ] [ការប្រើប្រាស់ output array (Python)](https://github.com/jwasham/practice-python/blob/master/merge_sort/merge_sort.py)
    - [ ] [In-place (C++)](https://github.com/jwasham/practice-cpp/blob/master/merge_sort/merge_sort.cc)
- [ ] កូដ Quick sort:
    - [ ] [Implementation (C)](http://www.cs.yale.edu/homes/aspnes/classes/223/examples/randomization/quick.c)
    - [ ] [Implementation (C)](https://github.com/jwasham/practice-c/blob/master/quick_sort/quick_sort.c)
    - [ ] [Implementation (Python)](https://github.com/jwasham/practice-python/blob/master/quick_sort/quick_sort.py)

- [ ] អនុវត្ត:
    - [ ] Mergesort: O(n log n) ករណីមធ្យម និង អាក្រក់បំផុត
    - [ ] Quicksort O(n log n) ករណីមធ្យម
    - Selection sort និង insertion sort ទាំងពីរគឺ O(n^2) សំរាប់ករណីមធ្យម និង អាក្រក់បំផុត
    - ចំពោះ heapsort, សូមមេីល Heap data structure ខាងលេី.

- [ ] មិនចាំបាច់ទេ ប៉ុន្តែខ្ញុំសូមណែនាំពួកគេ:
    - [ ] [Sedgewick - Radix Sorts (6 វីដេអូរ)](https://www.coursera.org/learn/algorithms-part2/home/week/3)
        - [ ] [1. Strings ក្នុង Java](https://www.coursera.org/learn/algorithms-part2/lecture/vGHvb/strings-in-java)
        - [ ] [2. ការរាប់ Key Indexed](https://www.coursera.org/learn/algorithms-part2/lecture/2pi1Z/key-indexed-counting)
        - [ ] [3. តម្រៀបខ្ទង់អក្សរដំបូងដែលមានខ្ទង់តិចបំផុត Radix Sort](https://www.coursera.org/learn/algorithms-part2/lecture/c1U7L/lsd-radix-sort)
        - [ ] [4. Most Significant Digit First String Radix Sort](https://www.coursera.org/learn/algorithms-part2/lecture/gFxwG/msd-radix-sort)
        - [ ] [5. វិធី ៣ Radix Quicksort](https://www.coursera.org/learn/algorithms-part2/lecture/crkd5/3-way-radix-quicksort)
        - [ ] [6. Suffix Arrays](https://www.coursera.org/learn/algorithms-part2/lecture/TH18W/suffix-arrays)
    - [ ] [Radix Sort](http://www.cs.yale.edu/homes/aspnes/classes/223/notes.html#radixSort)
    - [ ] [Radix Sort (វីដេអូរ)](https://www.youtube.com/watch?v=xhr26ia4k38)
    - [ ] [Radix Sort, Counting Sort (linear time given constraints) (វីដេអូរ)](https://www.youtube.com/watch?v=Nz1KZXbghj8&index=7&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb)
    - [ ] [Randomization: Matrix Multiply, Quicksort, Freivalds' algorithm (វីដេអូរ)](https://www.youtube.com/watch?v=cNB2lADK3_s&index=8&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp)
    - [ ] [Sorting in Linear Time (វីដេអូរ)](https://www.youtube.com/watch?v=pOKy3RZbSws&list=PLUl4u3cNGP61hsJNdULdudlRL493b-XZf&index=14)

ជាការសង្ខេបនេះគឺជាការបង្ហាញជាក់ស្តែងនៃ [១៥ វិធីដោះស្រាយ Sorting](https://www.youtube.com/watch?v=kPRA0W1kECg) ។
ប្រសិនបើអ្នកត្រូវការព័ត៌មានលម្អិតបន្ថែមលើប្រធានបទនេះសូមមើលផ្នែក "Sorting" នៅក្នុង [ព័ត៌មានលំអិតលើប្រធានបទមួយចំនួន](#additional-detail-on-some-subjects)

---

## Graphs

Graphs អាចត្រូវបានប្រើដើម្បីបង្ហាញពីបញ្ហាជាច្រើននៅក្នុងវិទ្យាសាស្ត្រកុំព្យូទ័រ ដូចជា Trees និង Sorting។

- កំណត់ចំណាំ:
    -  មានវិធីជាមូលដ្ឋានចំនួន ៤ ដើម្បីតំណាង graph ក្នុង memory:
        - objects និង pointers
        - adjacency matrix
        - adjacency list
        - adjacency map
    - ស្គាល់ខ្លួនឯងជាមួយនឹង Graphs និង គុណសម្បត្តិនិងគុណវិបត្តិរបស់វា
    - BFS និង DFS - ដឹងពីភាពស្មុគស្មាញក្នុងការគណនាការជួញដូររបស់ពួកគេ និង វិធីអនុវត្តកូដពិតប្រាកដ
    - នៅពេលសួរសំណួរសូមស្វែងរកដំណោះស្រាយដែលមានមូលដ្ឋានលើ Graphs ជាមុនសិនបន្ទាប់មកបន្តទៅមុខទៀតប្រសិនបើគ្មាន។ 

- [ ] MIT(វីដេអូ):
    - [ ] [ការស្វែងរក Breadth-First Search](https://www.youtube.com/watch?v=s-CYnVz-uh4&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=13)
    - [ ] [ការស្វែងរក Depth-First Search](https://www.youtube.com/watch?v=AfSk24UTFS8&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=14)

- [ ] ការបង្រៀន Skiena - ការណែនាំ:
    - [ ] [CSE373 2012 - មេរៀនទី 11 - Graph Data Structures (វីដេអូ)](https://www.youtube.com/watch?v=OiXxhDrFruw&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=11)
    - [ ] [CSE373 2012 - មេរៀនទី 12 - Breadth-First Search (វីដេអូ)](https://www.youtube.com/watch?v=g5vF8jscteo&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=12)
    - [ ] [CSE373 2012 - មេរៀនទី 13 - Graph Algorithms (វីដេអូ)](https://www.youtube.com/watch?v=S23W6eTcqdY&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=13)
    - [ ] [CSE373 2012 - មេរៀនទី 14 - Graph Algorithms (បន្ត) (វីដេអូ)](https://www.youtube.com/watch?v=WitPBKGV0HY&index=14&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b)
    - [ ] [CSE373 2012 - មេរៀនទី 15 - Graph Algorithms (បន្ត 2) (វីដេអូ)](https://www.youtube.com/watch?v=ia1L30l7OIg&index=15&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b)
    - [ ] [CSE373 2012 - មេរៀនទី 16 - Graph Algorithms (បន្ត 3) (វីដេអូ)](https://www.youtube.com/watch?v=jgDOQq6iWy8&index=16&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b)

- [ ] Graphs (ពិនិត្យឡើងវិញ និង ច្រើនទៀត):

    - [ ] [6.006 Single-Source Shortest Paths Problem (វីដេអូ)](https://www.youtube.com/watch?v=Aa2sqUhIn-E&index=15&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb)
    - [ ] [6.006 Dijkstra (វីដេអូ)](https://www.youtube.com/watch?v=2E7MmKv0Y24&index=16&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb)
    - [ ] [6.006 Bellman-Ford (វីដេអូ)](https://www.youtube.com/watch?v=ozsuci5pIso&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=17)
    - [ ] [6.006 Speeding Up Dijkstra (វីដេអូ)](https://www.youtube.com/watch?v=CHvQ3q_gJ7E&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=18)
    - [ ] [Aduni: Graph Algorithms I - Topological Sorting, Minimum Spanning Trees, Prim's Algorithm -  មេរៀនទី 6 (វីដេអូ)]( https://www.youtube.com/watch?v=i_AQT_XfvD8&index=6&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm)
    - [ ] [Aduni: Graph Algorithms II - DFS, BFS, Kruskal's Algorithm, Union Find Data Structure - មេរៀនទី 7 (វីដេអូ)]( https://www.youtube.com/watch?v=ufj5_bppBsA&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=7)
    - [ ] [Aduni: Graph Algorithms III: Shortest Path - មេរៀនទី 8 (វីដេអូ)](https://www.youtube.com/watch?v=DiedsPsMKXc&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=8)
    - [ ] [Aduni: Graph Alg. IV: Intro to geometric algorithms - មេរៀនទី 9 (វីដេអូ)](https://www.youtube.com/watch?v=XIAQRlNkJAw&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=9)
    - [ ] ~~[CS 61B 2014 (starting at 58:09) (វីដេអូ)](https://youtu.be/dgjX4HdMI-Q?list=PL-XXv-cvA_iAlnI-BQr9hjqADPBtujFJd&t=3489)~~
    - [ ] [CS 61B 2014: Weighted graphs (វីដេអូ)](https://archive.org/details/ucberkeley_webcast_zFbq8vOZ_0k)
    - [ ] [Greedy Algorithms: Minimum Spanning Tree (វីដេអូ)](https://www.youtube.com/watch?v=tKwnms5iRBU&index=16&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp)
    - [ ] [Strongly Connected Components Kosaraju's Algorithm Graph Algorithm (វីដេអូ)](https://www.youtube.com/watch?v=RpgcYiky7uw)

- វគ្គសិក្សា Coursera:
    - [ ] [Algorithms on Graphs (វីដេអូ)](https://www.coursera.org/learn/algorithms-on-graphs/home/welcome)

- ខ្ញុំនឹងអនុវត្ត:
    - [ ] DFS ជាមួយ adjacency list (recursive)
    - [ ] DFS ជាមួយ adjacency list (iterative with stack)
    - [ ] DFS ជាមួយ adjacency matrix (recursive)
    - [ ] DFS ជាមួយ adjacency matrix (iterative with stack)
    - [ ] BFS ជាមួយ adjacency list
    - [ ] BFS ជាមួយ adjacency matrix
    - [ ] single-source shortest path (Dijkstra)
    - [ ] minimum spanning tree
    - DFS-based algorithms (សូមមេីល Aduni វីដេអូ ខាងលេី):
        - [ ] ពិនិត្យ cycle (ត្រូវការសំរាប់ topological sort ព្រោះយើងនឹងពិនិត្យមើលវដ្តមុនពេលចាប់ផ្តើម)
        - [ ] topological sort
        - [ ] រាប់សមាសធាតុដែលបានភ្ជាប់នៅក្នុងក្រាហ្វ
        - [ ] រាយសមាសធាតុដែលភ្ជាប់គ្នាយ៉ាងខ្លាំង
        - [ ] ពិនិត្យក្រាហ្វិច bipartite

---

## Even More Knowledge
## ចំណេះដឹងបន្ធែម

- ### Recursion
    - [ ] ការបង្រៀនរបស់ Stanford លេី recursion និង backtracking:
        - [ ] [មេរៀនទី 8 | Programming Abstractions (វីដេអូ)](https://www.youtube.com/watch?v=gl3emqCuueQ&list=PLFE6E58F856038C69&index=8)
        - [ ] [មេរៀនទី 9 | Programming Abstractions (វីដេអូ)](https://www.youtube.com/watch?v=uFJhEPrbycQ&list=PLFE6E58F856038C69&index=9)
        - [ ] [មេរៀនទី 10 | Programming Abstractions (វីដេអូ)](https://www.youtube.com/watch?v=NdF1QDTRkck&index=10&list=PLFE6E58F856038C69)
        - [ ] [មេរៀនទី 11 | Programming Abstractions (វីដេអូ)](https://www.youtube.com/watch?v=p-gpaIGRCQI&list=PLFE6E58F856038C69&index=11)
    - នៅពេលដែលសមរម្យដើម្បីប្រើវា
    - តេី tail recursion ប្រសើរជាងអត់?
        - [ ] [អ្វីជា Tail Recursion និង ហេតុអ្វីបានជាវាអាក្រក់?](https://www.quora.com/What-is-tail-recursion-Why-is-it-so-bad)
        - [ ] [Tail Recursion (វីដេអូ)](https://www.youtube.com/watch?v=L1jjXGfxozc)

- ### Dynamic Programming
    - អ្នកប្រហែលជាមិនឃើញមានបញ្ហានៃការសរសេរកម្មវិធី dynamic programming នៅក្នុងបទសម្ភាសន៍របស់អ្នកទេ ប៉ុន្តែវាសមនឹងទទួលបានការទទួលស្គាល់នូវបញ្ហាមួយក្នុងនាមជាបេក្ខជនសម្រាប់ការសរសេរកម្មវិធី dynamic programming។
    - ប្រធានបទនេះអាចជាការពិបាកណាស់, ព្រោះថាបញ្ហារបស់ DP នីមួយៗត្រូវបានកំណត់ថាជាការទាក់ទងគ្នា
    - ខ្ញុំស្នើឱ្យក្រឡេកមើលឧទាហរណ៍ជាច្រើននៃបញ្ហា DP រហូតទាល់តែអ្នកមានការយល់ដឹងច្បាស់អំពីគំរូដែលពាក់ព័ន្ធ។
    - [ ] វីដេអូ:
        - វីដេអូ Skiena អាចពិបាកធ្វើតាមព្រោះពេលខ្លះគាត់ប្រើក្តារខៀនដែលវាមើលមិនឃើញ
        - [ ] [Skiena: CSE373 2012 - មេរៀនទី 19 - ការណែនាំអំពី Dynamic Programming (វីដេអូ)](https://youtu.be/Qc2ieXRgR0k?list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&t=1718)
        - [ ] [Skiena: CSE373 2012 - មេរៀនទី 20 - Edit Distance (video)](https://youtu.be/IsmMhMdyeGY?list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&t=2749)
        - [ ] [Skiena: CSE373 2012 - មេរៀនទី 21 - ឧទាហរណ៍ Dynamic Programming (វីដេអូ)](https://youtu.be/o0V9eYF4UI8?list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&t=406)
        - [ ] [Skiena: CSE373 2012 - មេរៀនទី 22 - ការអនុវត្តកម្មវិធី Dynamic Programming (វីដេអូ)](https://www.youtube.com/watch?v=dRbMC1Ltl3A&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=22)
        - [ ] [Simonson: Dynamic Programming 0 (ចាប់ផ្តេីមពី 59:18) (វីដេអូ)](https://youtu.be/J5aJEcOr6Eo?list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&t=3558)
        - [ ] [Simonson: Dynamic Programming I - មេរៀនទី 11 (វីដេអូ)](https://www.youtube.com/watch?v=0EzHjQ_SOeU&index=11&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm)
        - [ ] [Simonson: Dynamic programming II - មេរៀនទី 12 (វីដេអូ)](https://www.youtube.com/watch?v=v1qiRwuJU7g&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=12)
        - [ ] បញ្ជីបញ្ហារបស់ DP (នីមួយៗខ្លី):
            [Dynamic Programming (វីដេអូ)](https://www.youtube.com/playlist?list=PLrmLmBdmIlpsHaNTPP_jHHDx_os9ItYXr)
    - [ ] Yale Lecture notes:
        - [ ] [Dynamic Programming](http://www.cs.yale.edu/homes/aspnes/classes/223/notes.html#dynamicProgramming)
    - [ ] Coursera:
        - [ ] [បញ្ហា RNA secondary structure (វីដេអូ)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/80RrW/the-rna-secondary-structure-problem)
        - [ ] [A dynamic programming algorithm (វីដេអូ)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/PSonq/a-dynamic-programming-algorithm)
        - [ ] [បង្ហាញរូបភាពពីវិធីដោះស្រាយ DP (វីដេអូ)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/oUEK2/illustrating-the-dp-algorithm)
        - [ ] [ពេលវេលាដំណើរការនៃ DP algorithm (វីដេអូ)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/nfK2r/running-time-of-the-dp-algorithm)
        - [ ] [DP vs. recursive implementation (វីដេអូ)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/M999a/dp-vs-recursive-implementation)
        - [ ] [Global pairwise sequence alignment (វីដេអូ)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/UZ7o6/global-pairwise-sequence-alignment)
        - [ ] [Local pairwise sequence alignment (វីដេអូ)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/WnNau/local-pairwise-sequence-alignment)

- ### Object-Oriented Programming
    - [ ] [Optional: UML 2.0 Series (វីដេអូ)](https://www.youtube.com/watch?v=OkC7HKtiZC0&list=PLGLfVvz_LVvQ5G-LdJ8RLqe-ndo7QITYc)
    - [ ] គោលការណ៍ SOLID OOP: [គោលការណ៍ SOLID (វីដេអូ)](https://www.youtube.com/playlist?list=PL4CE9F710017EA77A)

- ### Design patterns
    - [ ] [ការពិនិត្យ Quick UML (វីដេអូ)](https://www.youtube.com/watch?v=3cmzqZzwNDM&list=PLGLfVvz_LVvQ5G-LdJ8RLqe-ndo7QITYc&index=3)
    - [ ] រៀនគំរូទាំងនេះ:
        - [ ] strategy
        - [ ] singleton
        - [ ] adapter
        - [ ] prototype
        - [ ] decorator
        - [ ] visitor
        - [ ] factory, abstract factory
        - [ ] facade
        - [ ] observer
        - [ ] proxy
        - [ ] delegate
        - [ ] command
        - [ ] state
        - [ ] memento
        - [ ] iterator
        - [ ] composite
        - [ ] flyweight
    - [ ] [ជំពូកទី ៦ (ភាគ ១) - Patterns (វីដេអូ)](https://youtu.be/LAP2A80Ajrg?list=PLJ9pm_Rc9HesnkwKlal_buSIHA-jTZMpO&t=3344)
    - [ ] [ជំពូកទី ៦ (ភាគ ២) - Abstraction-Occurrence, General Hierarchy, Player-Role, Singleton, Observer, Delegation (វីដេអូ)](https://www.youtube.com/watch?v=U8-PGsjvZc4&index=12&list=PLJ9pm_Rc9HesnkwKlal_buSIHA-jTZMpO)
    - [ ] [ជំពូកទី ៦ (ភាគ ៣) - Adapter, Facade, Immutable, Read-Only Interface, Proxy (video)](https://www.youtube.com/watch?v=7sduBHuex4c&index=13&list=PLJ9pm_Rc9HesnkwKlal_buSIHA-jTZMpO)
    - [ ] [ស៊េរីវីដេអូ (២៧ វីដេអូ)](https://www.youtube.com/playlist?list=PLF206E906175C7E07)
    - [ ] [Head First Design Patterns](https://www.amazon.com/Head-First-Design-Patterns-Freeman/dp/0596007124)
        - ខ្ញុំដឹងថាសៀវភៅបទបញ្ញត្តិគឺ“ លំនាំរចនា៖ ធាតុផ្សំនៃកម្មវិធីដែលអាចប្រើឡើងវិញបាន” ប៉ុន្តែក្បាលទីមួយគឺល្អសម្រាប់អ្នកចាប់ផ្តើមដំបូង Object-Oriented ។
    - [ ] [Handy reference: 101 Design Patterns & Tips for Developers](https://sourcemaking.com/design-patterns-and-tips)
    - [ ] [Design patterns សម្រាប់មនុស្ស](https://github.com/kamranahmedse/design-patterns-for-humans#structural-design-patterns)

- ### Combinatorics (n choose k) & Probability
    - [ ] [ជំនាញគណិតវិទ្យា៖ វិធីស្វែងរក Factorial, Permutation និង Combination (ជ្រើសរើស) (វីដេអូ)](https://www.youtube.com/watch?v=8RRo6Ti9d0U)
    - [ ] [Make School: Probability (វីដេអូ)](https://www.youtube.com/watch?v=sZkAAk9Wwa4)
    - [ ] [Make School: បន្ថែមលេី Probability និង Markov Chains (វីដេអូ)](https://www.youtube.com/watch?v=dNaJg-mLobQ)
    - [ ] Khan Academy:
        - ប្លង់វគ្គសិក្សា:
            - [ ] [ទ្រឹស្តីប្រូបាបដំបូង](https://www.khanacademy.org/math/probability/probability-and-combinatorics-topic)
        - គ្រាន់តែវីដេអូ - ៤១ (វីដេអូនីមួយៗមានលក្ខណៈសាមញ្ញហើយវីដេអូនីមួយៗខ្លី)៖
            - [ ] [ពន្យល់អំពីប្រូបាប (វីដេអូ)](https://www.youtube.com/watch?v=uzkc-qNVoOk&list=PLC58778F28211FA19)

- ### NP, NP-Complete និង Approximation Algorithms
    - ដឹងពីបញ្ហាល្បីរបស់ NP-complete, ដូចជាអ្នកលក់ធ្វើដំណើរ និង បញ្ហា knapsack, ហើយអាចស្គាល់ពួកគេនៅពេលអ្នកសម្ភាសសួរអ្នកដោយក្លែងបន្លំ។.
    - ដឹងថាអ្វីជា NP-complete.
    - [ ] [Computational Complexity (វីដេអូ)](https://www.youtube.com/watch?v=moPtwq_cVH8&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=23)
    - [ ] Simonson:
        - [ ] [Greedy Algs. II & Intro to NP Completeness (វីដេអូ)](https://youtu.be/qcGnJ47Smlo?list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&t=2939)
        - [ ] [NP Completeness II & Reductions (វីដេអូ)](https://www.youtube.com/watch?v=e0tGC6ZQdQE&index=16&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm)
        - [ ] [NP Completeness III (វីដេអូ)](https://www.youtube.com/watch?v=fCX1BGT3wjE&index=17&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm)
        - [ ] [NP Completeness IV (វីដេអូ)](https://www.youtube.com/watch?v=NKLDp3Rch3M&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=18)
    - [ ] Skiena:
        - [ ] [CSE373 2012 - មេរៀនទី 23 - Introduction to NP-Completeness (វីដេអូ)](https://youtu.be/KiK5TVgXbFg?list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&t=1508)
        - [ ] [CSE373 2012 - មេរៀនទី 24 - NP-Completeness Proofs (វីដេអូ)](https://www.youtube.com/watch?v=27Al52X3hd4&index=24&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b)
        - [ ] [CSE373 2012 - មេរៀនទី 25 - NP-Completeness Challenge (វីដេអូ)](https://www.youtube.com/watch?v=xCPH4gwIIXM&index=25&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b)
    - [ ] [Complexity: P, NP, NP-completeness, Reductions (វីដេអូ)](https://www.youtube.com/watch?v=eHZifpgyH_4&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=22)
    - [ ] [Complexity: Approximation Algorithms (វីដេអូ)](https://www.youtube.com/watch?v=MEz1J9wY2iM&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=24)
    - [ ] [Complexity: Fixed-Parameter Algorithms (វីដេអូ)](https://www.youtube.com/watch?v=4q-jmGrmxKs&index=25&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp)
    - Peter Norvig ពិភាក្សាអំពីដំណោះស្រាយដែលល្អប្រសើរបំផុតចំពោះបញ្ហាអ្នកលក់ធ្វើដំណើរ៖
        - [Jupyter Notebook](http://nbviewer.jupyter.org/url/norvig.com/ipython/TSP.ipynb)
    - ទំព័រ 1048 - 1140 ក្នុង CLRS ប្រសិនបើអ្នកមានវា.

- ### Caches
    - [ ] LRU cache:
        - [ ] [The Magic of LRU Cache (100 Days of Google Dev) (វីដេអូ)](https://www.youtube.com/watch?v=R5ON3iwx78M)
        - [ ] [Implementing LRU (វីដេអូ)](https://www.youtube.com/watch?v=bq6N7Ym81iI)
        - [ ] [LeetCode - 146 LRU Cache (C++) (វីដេអូ)](https://www.youtube.com/watch?v=8-FZRAjR7qU)
    - [ ] CPU cache:
        - [ ] [MIT 6.004 L15: The Memory Hierarchy (វីដេអូ)](https://www.youtube.com/watch?v=vjYF_fAZI5E&list=PLrRW1w6CGAcXbMtDFj205vALOGmiRc82-&index=24)
        - [ ] [MIT 6.004 L16: Cache Issues (វីដេអូ)](https://www.youtube.com/watch?v=ajgC3-pyGlk&index=25&list=PLrRW1w6CGAcXbMtDFj205vALOGmiRc82-)

- ### Processes and Threads
    - [ ] Computer Science 162 - Operating Systems (25 វីដេអូ):
        - សំរាប់ processes និង threads សូមមេីល វីដេអូ 1-11
        - [Operating Systems and System Programming (វីដេអូ)](https://archive.org/details/ucberkeley-webcast-PL-XXv-cvA_iBDyz-ba4yDskqMDY6A1w_c)
    - [តេី Process និង Thread ខុសគ្នាដូចម្តេច?](https://www.quora.com/What-is-the-difference-between-a-process-and-a-thread)
    - មាន:
        - Processes, Threads, Concurrency issues
            - តេី Process និង Thread ខុសគ្នាដូចម្តេច
            - Processes
            - Threads
            - Locks
            - Mutexes
            - Semaphores
            - Monitors
            - តើពួកគេធ្វើការយ៉ាងដូចម្តេច?
            - Deadlock
            - Livelock
        - CPU activity, interrupts, context switching
        - Modern concurrency constructs with multicore processors
        - [Paging, segmentation and virtual memory (វីដេអូ)](https://www.youtube.com/watch?v=LKe7xK0bF7o&list=PLCiOXwirraUCBE9i_ukL8_Kfg6XNv7Se8&index=2)
        - [Interrupts (វីដេអូ)](https://www.youtube.com/watch?v=uFKi2-J-6II&list=PLCiOXwirraUCBE9i_ukL8_Kfg6XNv7Se8&index=3)
        - Process resource needs (memory: code, static storage, stack, heap, and also file descriptors, i/o)
        - Thread resource needs (shares above (minus stack) with other threads in the same process but each has its own pc, stack counter, registers, and stack)
        - Forking is really copy on write (read-only) until the new process writes to memory, then it does a full copy.
        - Context switching
            - How context switching is initiated by the operating system and underlying hardware?
    - [ ] [threads in C++ (series - 10 វីដេអូ)](https://www.youtube.com/playlist?list=PL5jc9xFGsL8E12so1wlMS0r0hTQoJL74M)
    - [ ] concurrency ក្នុង Python (វីដេអូ):
        - [ ] [Short series on threads](https://www.youtube.com/playlist?list=PL1H1sBF1VAKVMONJWJkmUh6_p8g4F2oy1)
        - [ ] [Python Threads](https://www.youtube.com/watch?v=Bs7vPNbB9JM)
        - [ ] [Understanding the Python GIL (2010)](https://www.youtube.com/watch?v=Obt-vMVdM8s)
            - [reference](http://www.dabeaz.com/GIL)
        - [ ] [David Beazley - Python Concurrency From the Ground Up: LIVE! - PyCon 2015](https://www.youtube.com/watch?v=MCs5OvhV9S4)
        - [ ] [Keynote David Beazley - Topics of Interest (Python Asyncio)](https://www.youtube.com/watch?v=ZzfHjytDceU)
        - [ ] [Mutex in Python](https://www.youtube.com/watch?v=0zaPs8OtyKY)

- ### Testing
    - To cover:
        - តេី unit testing ដំណេីរការយ៉ាងដូចម្តេច ?
        - អ្វីជា mock objects ?
        - អ្វីជា integration testing ?
        - អ្វីជា dependency injection ?
    - [ ] [Agile Software Testing with James Bach (វីដេអូ)](https://www.youtube.com/watch?v=SAhJf36_u5U)
    - [ ] [Open Lecture by James Bach on Software Testing (វីដេអូ)](https://www.youtube.com/watch?v=ILkT_HV9DVU)
    - [ ] [Steve Freeman - Test-Driven Development (that’s not what we meant) (វីដេអូ)](https://vimeo.com/83960706)
        - [slides](http://gotocon.com/dl/goto-berlin-2013/slides/SteveFreeman_TestDrivenDevelopmentThatsNotWhatWeMeant.pdf)
    - [ ] Dependency injection:
        - [ ] [slides](https://www.youtube.com/watch?v=IKD2-MAkXyQ)
        - [ ] [Tao Of Testing](http://jasonpolites.github.io/tao-of-testing/ch3-1.1.html)
    - [ ] [How to write tests](http://jasonpolites.github.io/tao-of-testing/ch4-1.1.html)

- ### Scheduling (ការរៀបចំកាលវិភាគ)
    - នៅក្នុង OS, តេីវាដំណេីរការយ៉ាងដូចម្តេច ?
    - អាចប្រមូលបាន Operating System videos

- ### String searching & manipulations
    - [ ] [Sedgewick - Suffix Arrays (វីដេអូ)](https://www.coursera.org/learn/algorithms-part2/lecture/TH18W/suffix-arrays)
    - [ ] [Sedgewick - Substring Search (វីដេអូ)](https://www.coursera.org/learn/algorithms-part2/home/week/4)
        - [ ] [1. Introduction to Substring Search](https://www.coursera.org/learn/algorithms-part2/lecture/n3ZpG/introduction-to-substring-search)
        - [ ] [2. Brute-Force Substring Search](https://www.coursera.org/learn/algorithms-part2/lecture/2Kn5i/brute-force-substring-search)
        - [ ] [3. Knuth-Morris Pratt](https://www.coursera.org/learn/algorithms-part2/lecture/TAtDr/knuth-morris-pratt)
        - [ ] [4. Boyer-Moore](https://www.coursera.org/learn/algorithms-part2/lecture/CYxOT/boyer-moore)
        - [ ] [5. Rabin-Karp](https://www.coursera.org/learn/algorithms-part2/lecture/3KiqT/rabin-karp)
    - [ ] [Search pattern in text (វីដេអូ)](https://www.coursera.org/learn/data-structures/lecture/tAfHI/search-pattern-in-text)

    ប្រសិនបើអ្នកត្រូវការព័ត៌មានលម្អិតបន្ថែមលើប្រធានបទនេះសូមមើលផ្នែក [Additional Detail on Some Subjects](#additional-detail-on-some-subjects).

- ### Tries
    - ចំណាំ មានការ Tries ផ្សេងៗគ្នា។ អ្នកខ្លះមានprefixes អ្នកខ្លះមិនមាន ហើយអ្នកខ្លះប្រើstring ជំនួសឱ្យbits ដើម្បីតាមដានផ្លូវ
    - ខ្ញុំបានអានកូដប៉ុន្តែនឹងមិនអនុវត្តឡើយ
    - [ ] [Sedgewick - Tries (3 វីដេអូ)](https://www.coursera.org/learn/algorithms-part2/home/week/4)
        - [ ] [1. R Way Tries](https://www.coursera.org/learn/algorithms-part2/lecture/CPVdr/r-way-tries)
        - [ ] [2. Ternary Search Tries](https://www.coursera.org/learn/algorithms-part2/lecture/yQM8K/ternary-search-tries)
        - [ ] [3. Character Based Operations](https://www.coursera.org/learn/algorithms-part2/lecture/jwNmV/character-based-operations)
    - [ ] [Notes on Data Structures and Programming Techniques](http://www.cs.yale.edu/homes/aspnes/classes/223/notes.html#Tries)
    - [ ] វីដេអូខ្លីៗ:
        - [ ] [Introduction To Tries (វីដេអូ)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/08Xyf/core-introduction-to-tries)
        - [ ] [Performance Of Tries (វីដេអូ)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/PvlZW/core-performance-of-tries)
        - [ ] [Implementing A Trie (វីដេអូ)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/DFvd3/core-implementing-a-trie)
    - [ ] [The Trie: A Neglected Data Structure](https://www.toptal.com/java/the-trie-a-neglected-data-structure)
    - [ ] [TopCoder - Using Tries](https://www.topcoder.com/community/competitive-programming/tutorials/using-tries/)
    - [ ] [Stanford Lecture (real world use case) (វីដេអូ)](https://www.youtube.com/watch?v=TJ8SkcUSdbU)
    - [ ] [MIT, Advanced Data Structures, Strings (can get pretty obscure about halfway through) (វីដេអូ)](https://www.youtube.com/watch?v=NinWEPPrkDQ&index=16&list=PLUl4u3cNGP61hsJNdULdudlRL493b-XZf)

- ### Floating Point Numbers
    - [ ] simple 8-bit: [Representation of Floating Point Numbers - 1 (វីដេអូ - មានកំហុសក្នុងការគណនា - សូមមើលការពិពណ៌នាជាវីដេអូ)](https://www.youtube.com/watch?v=ji3SfClm8TU)
    - [ ] 32 bit: [IEEE754 32-bit floating point binary (វីដេអូ)](https://www.youtube.com/watch?v=50ZYcZebIec)

- ### Unicode
    - [ ] [The Absolute Minimum Every Software Developer Absolutely, Positively Must Know About Unicode and Character Sets]( http://www.joelonsoftware.com/articles/Unicode.html)
    - [ ] [What Every Programmer Absolutely, Positively Needs To Know About Encodings And Character Sets To Work With Text](http://kunststube.net/encoding/)

- ### Endianness
    - [ ] [Big And Little Endian](https://web.archive.org/web/20180107141940/http://www.cs.umd.edu:80/class/sum2003/cmsc311/Notes/Data/endian.html)
    - [ ] [Big Endian Vs Little Endian (វីដេអូ)](https://www.youtube.com/watch?v=JrNF0KRAlyo)
    - [ ] [Big And Little Endian Inside/Out (វីដេអូ)](https://www.youtube.com/watch?v=oBSuXP-1Tc0)
        - និយាយបច្ចេកទេសខ្លាំងណាស់សម្រាប់ kernel devs. កុំបារម្ភប្រសិនបេីមិនយល់ទាំងស្រុង
        - ពាក់កណ្តាលទីមួយគឺគ្រប់គ្រាន់ហើយ

- ### Networking (បណ្តាញ)
    - ** ប្រសិនបើអ្នកមានបទពិសោធបណ្តាញឬចង់ក្លាយជាវិស្វករដែលអាចជឿជាក់បានឬវិស្វករប្រតិបត្តិការរំពឹងថានឹងមានសំណួរ **
    - បើមិនដូច្នោះទេនេះគ្រាន់តែជាការល្អដើម្បីដឹង
    - [ ] [Khan Academy](https://www.khanacademy.org/computing/computer-science/computers-and-internet-code-org)
    - [ ] [UDP and TCP: Comparison of Transport Protocols (វីដេអូ)](https://www.youtube.com/watch?v=Vdc8TCESIg8)
    - [ ] [TCP/IP and the OSI Model Explained! (វីដេអូ)](https://www.youtube.com/watch?v=e5DEVa9eSN0)
    - [ ] [Packet Transmission across the Internet. Networking & TCP/IP tutorial. (វីដេអូ)](https://www.youtube.com/watch?v=nomyRJehhnM)
    - [ ] [HTTP (វីដេអូ)](https://www.youtube.com/watch?v=WGJrLqtX7As)
    - [ ] [SSL and HTTPS (វីដេអូ)](https://www.youtube.com/watch?v=S2iBR2ZlZf0)
    - [ ] [SSL/TLS (វីដេអូ)](https://www.youtube.com/watch?v=Rp3iZUvXWlM)
    - [ ] [HTTP 2.0 (វីដេអូ)](https://www.youtube.com/watch?v=E9FxNzv1Tr8)
    - [ ] [Video Series (21 វីដេអូ) (វីដេអូ)](https://www.youtube.com/playlist?list=PLEbnTDJUr_IegfoqO4iPnPYQui46QqT0j)
    - [ ] [Subnetting Demystified - Part 5 CIDR Notation (វីដេអូ)](https://www.youtube.com/watch?v=t5xYI0jzOf4)
    - [ ] Sockets:
        - [ ] [Java - Sockets - Introduction (វីដេអូ)](https://www.youtube.com/watch?v=6G_W54zuadg&t=6s)
        - [ ] [Socket Programming (វីដេអូ)](https://www.youtube.com/watch?v=G75vN2mnJeQ)

## System Design, Scalability, Data Handling

** អ្នកអាចរំពឹងថានឹងមានសំណួររចនាប្រព័ន្ធប្រសិនបើអ្នកមានបទពិសោធ 4+ ឆ្នាំ។ **

- Scalability និង System Designគឺជាប្រធានបទដែលមានប្រធានបទជាច្រេីន និង ធនធានជាច្រើន ដោយសារវាត្រូវការគិតច្រេីនពេលបង្កេីតប្រព័ន្ធដែលល្អ
  រំពឹងថានឹងចំណាយពេលបន្តិចលើរឿងនេះ
- ការពិចារណា:
    - Scalability
        - Distill large data sets to single values
        - Transform one data set to another
        - Handling obscenely large amounts of data
    - System design
        - features sets
        - interfaces
        - class hierarchies
        - designing a system under certain constraints
        - simplicity and robustness
        - tradeoffs
        - performance analysis and optimization
- [ ] **ចាប់ផ្តើមនៅទីនេះ**: [The System Design Primer](https://github.com/donnemartin/system-design-primer)
- [ ] [System Design from HiredInTech](http://www.hiredintech.com/system-design/)
- [ ] [How Do I Prepare To Answer Design Questions In A Technical Inverview?](https://www.quora.com/How-do-I-prepare-to-answer-design-questions-in-a-technical-interview?redirected_qid=1500023)
- [ ] [8 Things You Need to Know Before a System Design Interview](http://blog.gainlo.co/index.php/2015/10/22/8-things-you-need-to-know-before-system-design-interviews/)
- [ ] [Algorithm design](http://www.hiredintech.com/algorithm-design/)
- [ ] [Database Normalization - 1NF, 2NF, 3NF and 4NF (វីដេអូ)](https://www.youtube.com/watch?v=UrYLYV7WSHM)
- [ ] [System Design Interview](https://github.com/checkcheckzz/system-design-interview) - There are a lot of resources in this one. Look through the articles and examples. I put some of them below
- [ ] [How to ace a systems design interview](http://www.palantir.com/2011/10/how-to-rock-a-systems-design-interview/)
- [ ] [Numbers Everyone Should Know](http://everythingisdata.wordpress.com/2009/10/17/numbers-everyone-should-know/)
- [ ] [How long does it take to make a context switch?](http://blog.tsunanet.net/2010/11/how-long-does-it-take-to-make-context.html)
- [ ] [Transactions Across Datacenters (វីដេអូ)](https://www.youtube.com/watch?v=srOgpXECblk)
- [ ] [A plain English introduction to CAP Theorem](http://ksat.me/a-plain-english-introduction-to-cap-theorem/)
- [ ] Consensus Algorithms:
    - [ ] Paxos - [Paxos Agreement - Computerphile (វីដេអូ)](https://www.youtube.com/watch?v=s8JqcZtvnsM)
    - [ ] Raft - [An Introduction to the Raft Distributed Consensus Algorithm (វីដេអូ)](https://www.youtube.com/watch?v=P9Ydif5_qvE)
        - [ ] [Easy-to-read paper](https://raft.github.io/)
        - [ ] [Infographic](http://thesecretlivesofdata.com/raft/)
- [ ] [Consistent Hashing](http://www.tom-e-white.com/2007/11/consistent-hashing.html)
- [ ] [NoSQL Patterns](http://horicky.blogspot.com/2009/11/nosql-patterns.html)
- [ ] Scalability:
    - You don't need all of these. Just pick a few that interest you.
    - [ ] [Great overview (វីដេអូ)](https://www.youtube.com/watch?v=-W9F__D3oY4)
    - [ ] Short series:
        - [Clones](http://www.lecloud.net/post/7295452622/scalability-for-dummies-part-1-clones)
        - [Database](http://www.lecloud.net/post/7994751381/scalability-for-dummies-part-2-database)
        - [Cache](http://www.lecloud.net/post/9246290032/scalability-for-dummies-part-3-cache)
        - [Asynchronism](http://www.lecloud.net/post/9699762917/scalability-for-dummies-part-4-asynchronism)
    - [ ] [Scalable Web Architecture and Distributed Systems](http://www.aosabook.org/en/distsys.html)
    - [ ] [Fallacies of Distributed Computing Explained](https://pages.cs.wisc.edu/~zuyu/files/fallacies.pdf)
    - [ ] [Pragmatic Programming Techniques](http://horicky.blogspot.com/2010/10/scalable-system-design-patterns.html)
        - [extra: Google Pregel Graph Processing](http://horicky.blogspot.com/2010/07/google-pregel-graph-processing.html)
    - [ ] [Jeff Dean - Building Software Systems At Google and Lessons Learned (វីដេអូ)](https://www.youtube.com/watch?v=modXC5IWTJI)
    - [ ] [Introduction to Architecting Systems for Scale](http://lethain.com/introduction-to-architecting-systems-for-scale/)
    - [ ] [Scaling mobile games to a global audience using App Engine and Cloud Datastore (វីដេអូ)](https://www.youtube.com/watch?v=9nWyWwY2Onc)
    - [ ] [How Google Does Planet-Scale Engineering for Planet-Scale Infra (វីដេអូ)](https://www.youtube.com/watch?v=H4vMcD7zKM0)
    - [ ] [The Importance of Algorithms](https://www.topcoder.com/community/competitive-programming/tutorials/the-importance-of-algorithms/)
    - [ ] [Sharding](http://highscalability.com/blog/2009/8/6/an-unorthodox-approach-to-database-design-the-coming-of-the.html)
    - [ ] [Scale at Facebook (2012), "Building for a Billion Users" (វីដេអូ)](https://www.youtube.com/watch?v=oodS71YtkGU)
    - [ ] [Engineering for the Long Game - Astrid Atkinson Keynote(វីដេអូ)](https://www.youtube.com/watch?v=p0jGmgIrf_M&list=PLRXxvay_m8gqVlExPC5DG3TGWJTaBgqSA&index=4)
    - [ ] [7 Years Of YouTube Scalability Lessons In 30 Minutes](http://highscalability.com/blog/2012/3/26/7-years-of-youtube-scalability-lessons-in-30-minutes.html)
        - [video](https://www.youtube.com/watch?v=G-lGCC4KKok)
    - [ ] [How PayPal Scaled To Billions Of Transactions Daily Using Just 8VMs](http://highscalability.com/blog/2016/8/15/how-paypal-scaled-to-billions-of-transactions-daily-using-ju.html)
    - [ ] [How to Remove Duplicates in Large Datasets](https://blog.clevertap.com/how-to-remove-duplicates-in-large-datasets/)
    - [ ] [A look inside Etsy's scale and engineering culture with Jon Cowie (វីដេអូ)](https://www.youtube.com/watch?v=3vV4YiqKm1o)
    - [ ] [What Led Amazon to its Own Microservices Architecture](http://thenewstack.io/led-amazon-microservices-architecture/)
    - [ ] [To Compress Or Not To Compress, That Was Uber's Question](https://eng.uber.com/trip-data-squeeze/)
    - [ ] [Asyncio Tarantool Queue, Get In The Queue](http://highscalability.com/blog/2016/3/3/asyncio-tarantool-queue-get-in-the-queue.html)
    - [ ] [When Should Approximate Query Processing Be Used?](http://highscalability.com/blog/2016/2/25/when-should-approximate-query-processing-be-used.html)
    - [ ] [Google's Transition From Single Datacenter, To Failover, To A Native Multihomed Architecture]( http://highscalability.com/blog/2016/2/23/googles-transition-from-single-datacenter-to-failover-to-a-n.html)
    - [ ] [Spanner](http://highscalability.com/blog/2012/9/24/google-spanners-most-surprising-revelation-nosql-is-out-and.html)
    - [ ] [Machine Learning Driven Programming: A New Programming For A New World](http://highscalability.com/blog/2016/7/6/machine-learning-driven-programming-a-new-programming-for-a.html)
    - [ ] [The Image Optimization Technology That Serves Millions Of Requests Per Day](http://highscalability.com/blog/2016/6/15/the-image-optimization-technology-that-serves-millions-of-re.html)
    - [ ] [A Patreon Architecture Short](http://highscalability.com/blog/2016/2/1/a-patreon-architecture-short.html)
    - [ ] [Tinder: How Does One Of The Largest Recommendation Engines Decide Who You'll See Next?](http://highscalability.com/blog/2016/1/27/tinder-how-does-one-of-the-largest-recommendation-engines-de.html)
    - [ ] [Design Of A Modern Cache](http://highscalability.com/blog/2016/1/25/design-of-a-modern-cache.html)
    - [ ] [Live Video Streaming At Facebook Scale](http://highscalability.com/blog/2016/1/13/live-video-streaming-at-facebook-scale.html)
    - [ ] [A Beginner's Guide To Scaling To 11 Million+ Users On Amazon's AWS](http://highscalability.com/blog/2016/1/11/a-beginners-guide-to-scaling-to-11-million-users-on-amazons.html)
    - [ ] [How Does The Use Of Docker Effect Latency?](http://highscalability.com/blog/2015/12/16/how-does-the-use-of-docker-effect-latency.html)
    - [ ] [A 360 Degree View Of The Entire Netflix Stack](http://highscalability.com/blog/2015/11/9/a-360-degree-view-of-the-entire-netflix-stack.html)
    - [ ] [Latency Is Everywhere And It Costs You Sales - How To Crush It](http://highscalability.com/latency-everywhere-and-it-costs-you-sales-how-crush-it)
    - [ ] [Serverless (very long, just need the gist)](http://martinfowler.com/articles/serverless.html)
    - [ ] [What Powers Instagram: Hundreds of Instances, Dozens of Technologies](http://instagram-engineering.tumblr.com/post/13649370142/what-powers-instagram-hundreds-of-instances)
    - [ ] [Cinchcast Architecture - Producing 1,500 Hours Of Audio Every Day](http://highscalability.com/blog/2012/7/16/cinchcast-architecture-producing-1500-hours-of-audio-every-d.html)
    - [ ] [Justin.Tv's Live Video Broadcasting Architecture](http://highscalability.com/blog/2010/3/16/justintvs-live-video-broadcasting-architecture.html)
    - [ ] [Playfish's Social Gaming Architecture - 50 Million Monthly Users And Growing](http://highscalability.com/blog/2010/9/21/playfishs-social-gaming-architecture-50-million-monthly-user.html)
    - [ ] [TripAdvisor Architecture - 40M Visitors, 200M Dynamic Page Views, 30TB Data](http://highscalability.com/blog/2011/6/27/tripadvisor-architecture-40m-visitors-200m-dynamic-page-view.html)
    - [ ] [PlentyOfFish Architecture](http://highscalability.com/plentyoffish-architecture)
    - [ ] [Salesforce Architecture - How They Handle 1.3 Billion Transactions A Day](http://highscalability.com/blog/2013/9/23/salesforce-architecture-how-they-handle-13-billion-transacti.html)
    - [ ] [ESPN's Architecture At Scale - Operating At 100,000 Duh Nuh Nuhs Per Second](http://highscalability.com/blog/2013/11/4/espns-architecture-at-scale-operating-at-100000-duh-nuh-nuhs.html)
    - [ ] See "Messaging, Serialization, and Queueing Systems" way below for info on some of the technologies that can glue services together
    - [ ] Twitter:
        - [O'Reilly MySQL CE 2011: Jeremy Cole, "Big and Small Data at @Twitter" (វីដេអូ)](https://www.youtube.com/watch?v=5cKTP36HVgI)
        - [Timelines at Scale](https://www.infoq.com/presentations/Twitter-Timeline-Scalability)
    - For even more, see "Mining Massive Datasets" video series in the [វីដេអូ](#video-series) section
- [ ] Practicing the system design process: Here are some ideas to try working through on paper, each with some documentation on how it was handled in the real world:
    - review: [The System Design Primer](https://github.com/donnemartin/system-design-primer)
    - [System Design from HiredInTech](http://www.hiredintech.com/system-design/)
    - [cheat sheet](https://github.com/jwasham/coding-interview-university/blob/master/extras/cheat%20sheets/system-design.pdf)
    - flow:
        1. Understand the problem and scope:
            - Define the use cases, with interviewer's help
            - Suggest additional features
            - Remove items that interviewer deems out of scope
            - Assume high availability is required, add as a use case
        2. Think about constraints:
            - Ask how many requests per month
            - Ask how many requests per second (they may volunteer it or make you do the math)
            - Estimate reads vs. writes percentage
            - Keep 80/20 rule in mind when estimating
            - How much data written per second
            - Total storage required over 5 years
            - How much data read per second
        3. Abstract design:
            - Layers (service, data, caching)
            - Infrastructure: load balancing, messaging
            - Rough overview of any key algorithm that drives the service
            - Consider bottlenecks and determine solutions
    - Exercises:
        - [Design a CDN network: old article](https://kilthub.cmu.edu/articles/Globally_distributed_content_delivery/6605972)
        - [Design a random unique ID generation system](https://blog.twitter.com/2010/announcing-snowflake)
        - [Design an online multiplayer card game](http://www.indieflashblog.com/how-to-create-an-asynchronous-multiplayer-game.html)
        - [Design a key-value database](http://www.slideshare.net/dvirsky/introduction-to-redis)
        - [Design a picture sharing system](http://highscalability.com/blog/2011/12/6/instagram-architecture-14-million-users-terabytes-of-photos.html)
        - [Design a recommendation system](http://ijcai13.org/files/tutorial_slides/td3.pdf)
        - [Design a URL-shortener system: copied from above](http://www.hiredintech.com/system-design/the-system-design-process/)
        - [Design a cache system](https://www.adayinthelifeof.nl/2011/02/06/memcache-internals/)

---

## Final Review

    This section will have shorter videos that you can watch pretty quickly to review most of the important concepts.
    It's nice if you want a refresher often.

- [ ] Series of 2-3 minutes short subject videos (23 videos)
    - [Videos](https://www.youtube.com/watch?v=r4r1DZcx1cM&list=PLmVb1OknmNJuC5POdcDv5oCS7_OUkDgpj&index=22)
- [ ] Series of 2-5 minutes short subject videos - Michael Sambol (18 videos):
    - [Videos](https://www.youtube.com/channel/UCzDJwLWoYCUQowF_nG3m5OQ)
- [ ] [Sedgewick Videos - Algorithms I](https://www.coursera.org/learn/algorithms-part1)
- [ ] [Sedgewick Videos - Algorithms II](https://www.coursera.org/learn/algorithms-part2)

---

## Coding Question Practice

Now that you know all the computer science topics above, it's time to practice answering coding problems.

**Coding question practice is not about memorizing answers to programming problems.**

Why you need to practice doing programming problems:
- Problem recognition, and where the right data structures and algorithms fit in
- Gathering requirements for the problem
- Talking your way through the problem like you will in the interview
- Coding on a whiteboard or paper, not a computer
- Coming up with time and space complexity for your solutions
- Testing your solutions

There is a great intro for methodical, communicative problem solving in an interview. You'll get this from the programming
interview books, too, but I found this outstanding:
[Algorithm design canvas](http://www.hiredintech.com/algorithm-design/)

No whiteboard at home? That makes sense. I'm a weirdo and have a big whiteboard. Instead of a whiteboard, pick up a
large drawing pad from an art store. You can sit on the couch and practice. This is my "sofa whiteboard".
I added the pen in the photo for scale. If you use a pen, you'll wish you could erase. Gets messy quick. I use a pencil 
and eraser.

![my sofa whiteboard](https://d3j2pkmjtin6ou.cloudfront.net/art_board_sm_2.jpg)

Supplemental:

- [Mathematics for Topcoders](https://www.topcoder.com/community/competitive-programming/tutorials/mathematics-for-topcoders/)
- [Dynamic Programming – From Novice to Advanced](https://www.topcoder.com/community/competitive-programming/tutorials/dynamic-programming-from-novice-to-advanced/)
- [MIT Interview Materials](https://web.archive.org/web/20160906124824/http://courses.csail.mit.edu/iap/interview/materials.php)
- [Exercises for getting better at a given language](http://exercism.io/languages)

**Read and Do Programming Problems (in this order):**

- [ ] [Programming Interviews Exposed: Secrets to Landing Your Next Job, 2nd Edition](http://www.wiley.com/WileyCDA/WileyTitle/productCd-047012167X.html)
    - answers in C, C++ and Java
- [ ] [Cracking the Coding Interview, 6th Edition](http://www.amazon.com/Cracking-Coding-Interview-6th-Programming/dp/0984782850/)
    - answers in Java

See [Book List above](#book-list)


## Coding exercises/challenges

Once you've learned your brains out, put those brains to work.
Take coding challenges every day, as many as you can.

- [How to Find a Solution](https://www.topcoder.com/community/competitive-programming/tutorials/how-to-find-a-solution/)
- [How to Dissect a Topcoder Problem Statement](https://www.topcoder.com/community/competitive-programming/tutorials/how-to-dissect-a-topcoder-problem-statement/)

Coding Interview Question Videos:
- [IDeserve (88 videos)](https://www.youtube.com/watch?v=NBcqBddFbZw&list=PLamzFoFxwoNjPfxzaWqs7cZGsPYy0x_gI)
- [Tushar Roy (5 playlists)](https://www.youtube.com/user/tusharroy2525/playlists?shelf_id=2&view=50&sort=dd)
    - Super for walkthroughs of problem solutions
- [Nick White - LeetCode Solutions (187 Videos)](https://www.youtube.com/playlist?list=PLU_sdQYzUj2keVENTP0a5rdykRSgg9Wp-)
    - Good explanations of solution and the code
    - You can watch several in a short time
- [FisherCoder - LeetCode Solutions](https://youtube.com/FisherCoder)

Challenge sites:
- [LeetCode](https://leetcode.com/)
    - My favorite coding problem site. It's worth the subscription money for the 1-2 months you'll likely be preparing
    - [LeetCode solutions from FisherCoder](https://github.com/fishercoder1534/Leetcode) 
    - See Nick White Videos above for short code-throughs
- [HackerRank](https://www.hackerrank.com/)
- [TopCoder](https://www.topcoder.com/)
- [InterviewCake](https://www.interviewcake.com/)
- [Geeks for Geeks](http://www.geeksforgeeks.org/)
- [InterviewBit](https://www.interviewbit.com/invite/icjf)
- [Project Euler (math-focused)](https://projecteuler.net/index.php?section=problems)
- [Code Exercises](https://code-exercises.com)

Language-learning sites, with challenges:
- [Codewars](http://www.codewars.com)
- [Codility](https://codility.com/programmers/)
- [HackerEarth](https://www.hackerearth.com/)
- [Sphere Online Judge (spoj)](http://www.spoj.com/)
- [Codechef](https://www.codechef.com/)

Challenge repos:
- [Interactive Coding Interview Challenges in Python](https://github.com/donnemartin/interactive-coding-challenges)

Mock Interviews:
- [Gainlo.co: Mock interviewers from big companies](http://www.gainlo.co/) - I used this and it helped me relax for the phone screen and on-site interview
- [Pramp: Mock interviews from/with peers](https://www.pramp.com/) - peer-to-peer model of practice interviews
- [Refdash: Mock interviews and expedited interviews](https://refdash.com/) - also help candidates fast track by skipping multiple interviews with tech companies
- [interviewing.io: Practice mock interview with senior engineers](https://interviewing.io) - anonymous algorithmic/systems design interviews with senior engineers from FAANG anonymously. 


## Once you're closer to the interview

- Cracking The Coding Interview Set 2 (videos):
    - [Cracking The Code Interview](https://www.youtube.com/watch?v=4NIb9l3imAo)
    - [Cracking the Coding Interview - Fullstack Speaker Series](https://www.youtube.com/watch?v=Eg5-tdAwclo)

## Your Resume

- See Resume prep items in Cracking The Coding Interview and back of Programming Interviews Exposed


## Be thinking of for when the interview comes

Think of about 20 interview questions you'll get, along with the lines of the items below. Have 2-3 answers for each.
Have a story, not just data, about something you accomplished.

- Why do you want this job?
- What's a tough problem you've solved?
- Biggest challenges faced?
- Best/worst designs seen?
- Ideas for improving an existing product
- How do you work best, as an individual and as part of a team?
- Which of your skills or experiences would be assets in the role and why?
- What did you most enjoy at [job x / project y]?
- What was the biggest challenge you faced at [job x / project y]?
- What was the hardest bug you faced at [job x / project y]?
- What did you learn at [job x / project y]?
- What would you have done better at [job x / project y]?

## Have questions for the interviewer

    Some of mine (I already may know answer to but want their opinion or team perspective):

- How large is your team?
- What does your dev cycle look like? Do you do waterfall/sprints/agile?
- Are rushes to deadlines common? Or is there flexibility?
- How are decisions made in your team?
- How many meetings do you have per week?
- Do you feel your work environment helps you concentrate?
- What are you working on?
- What do you like about it?
- What is the work life like?
- How is work/life balance?

## Once You've Got The Job

Congratulations!

Keep learning.

You're never really done.

---

    *****************************************************************************************************
    *****************************************************************************************************

    Everything below this point is optional.
    By studying these, you'll get greater exposure to more CS concepts, and will be better prepared for
    any software engineering job. You'll be a much more well-rounded software engineer.

    *****************************************************************************************************
    *****************************************************************************************************

---

## Additional Books

    These are here so you can dive into a topic you find interesting.

- [The Unix Programming Environment](https://www.amazon.com/dp/013937681X)
    - An oldie but a goodie
- [The Linux Command Line: A Complete Introduction](https://www.amazon.com/dp/1593273894/)
    - A modern option
- [TCP/IP Illustrated Series](https://en.wikipedia.org/wiki/TCP/IP_Illustrated)
- [Head First Design Patterns](https://www.amazon.com/gp/product/0596007124/)
    - A gentle introduction to design patterns
- [Design Patterns: Elements of Reusable Object-Oriente​d Software](https://www.amazon.com/Design-Patterns-Elements-Reusable-Object-Oriented/dp/0201633612)
    - AKA the "Gang Of Four" book, or GOF
    - The canonical design patterns book
- [UNIX and Linux System Administration Handbook, 5th Edition](https://www.amazon.com/UNIX-Linux-System-Administration-Handbook/dp/0134277554/)
- [Algorithm Design Manual](http://www.amazon.com/Algorithm-Design-Manual-Steven-Skiena/dp/1849967202) (Skiena)
    - As a review and problem recognition
    - The algorithm catalog portion is well beyond the scope of difficulty you'll get in an interview
    - This book has 2 parts:
        - Class textbook on data structures and algorithms
            - Pros:
                - Is a good review as any algorithms textbook would be
                - Nice stories from his experiences solving problems in industry and academia
                - Code examples in C
            - Cons:
                - Can be as dense or impenetrable as CLRS, and in some cases, CLRS may be a better alternative for some subjects
                - Chapters 7, 8, 9 can be painful to try to follow, as some items are not explained well or require more brain than I have
                - Don't get me wrong: I like Skiena, his teaching style, and mannerisms, but I may not be Stony Brook material
        - Algorithm catalog:
            - This is the real reason you buy this book
            - About to get to this part. Will update here once I've made my way through it
    - Can rent it on kindle
    - Answers:
        - [Solutions](http://www.algorithm.cs.sunysb.edu/algowiki/index.php/The_Algorithms_Design_Manual_(Second_Edition))
        - [Solutions](http://blog.panictank.net/category/algorithmndesignmanualsolutions/page/2/)
    - [Errata](http://www3.cs.stonybrook.edu/~skiena/algorist/book/errata)
- [Write Great Code: Volume 1: Understanding the Machine](https://www.amazon.com/Write-Great-Code-Understanding-Machine/dp/1593270038)
    - The book was published in 2004, and is somewhat outdated, but it's a terrific resource for understanding a computer in brief
    - The author invented [HLA](https://en.wikipedia.org/wiki/High_Level_Assembly), so take mentions and examples in HLA with a grain of salt. Not widely used, but decent examples of what assembly looks like
    - These chapters are worth the read to give you a nice foundation:
        - Chapter 2 - Numeric Representation
        - Chapter 3 - Binary Arithmetic and Bit Operations
        - Chapter 4 - Floating-Point Representation
        - Chapter 5 - Character Representation
        - Chapter 6 - Memory Organization and Access
        - Chapter 7 - Composite Data Types and Memory Objects
        - Chapter 9 - CPU Architecture
        - Chapter 10 - Instruction Set Architecture
        - Chapter 11 - Memory Architecture and Organization
- [Introduction to Algorithms](https://www.amazon.com/Introduction-Algorithms-3rd-MIT-Press/dp/0262033844)
    - **Important:** Reading this book will only have limited value. This book is a great review of algorithms and data structures, but won't teach you how to write good code. You have to be able to code a decent solution efficiently
    - AKA CLR, sometimes CLRS, because Stein was late to the game

- [Computer Architecture, Sixth Edition: A Quantitative Approach](https://www.amazon.com/dp/0128119055)
    - For a richer, more up-to-date (2017), but longer treatment

- [Programming Pearls](http://www.amazon.com/Programming-Pearls-2nd-Jon-Bentley/dp/0201657880)
    - The first couple of chapters present clever solutions to programming problems (some very old using data tape) but
      that is just an intro. This a guidebook on program design and architecture

## Additional Learning
    
    I added them to help you become a well-rounded software engineer, and to be aware of certain 
    technologies and algorithms, so you'll have a bigger toolbox.

- ### Compilers
    - [How a Compiler Works in ~1 minute (video)](https://www.youtube.com/watch?v=IhC7sdYe-Jg)
    - [Harvard CS50 - Compilers (video)](https://www.youtube.com/watch?v=CSZLNYF4Klo)
    - [C++ (video)](https://www.youtube.com/watch?v=twodd1KFfGk)
    - [Understanding Compiler Optimization (C++) (video)](https://www.youtube.com/watch?v=FnGCDLhaxKU)

- ### Emacs and vi(m)
    - Familiarize yourself with a unix-based code editor
    - vi(m):
        - [Editing With vim 01 - Installation, Setup, and The Modes (video)](https://www.youtube.com/watch?v=5givLEMcINQ&index=1&list=PL13bz4SHGmRxlZVmWQ9DvXo1fEg4UdGkr)
        - [VIM Adventures](http://vim-adventures.com/)
        - set of 4 videos:
            - [The vi/vim editor - Lesson 1](https://www.youtube.com/watch?v=SI8TeVMX8pk)
            - [The vi/vim editor - Lesson 2](https://www.youtube.com/watch?v=F3OO7ZIOaJE)
            - [The vi/vim editor - Lesson 3](https://www.youtube.com/watch?v=ZYEccA_nMaI)
            - [The vi/vim editor - Lesson 4](https://www.youtube.com/watch?v=1lYD5gwgZIA)
        - [Using Vi Instead of Emacs](http://www.cs.yale.edu/homes/aspnes/classes/223/notes.html#Using_Vi_instead_of_Emacs)
    - emacs:
        - [Basics Emacs Tutorial (video)](https://www.youtube.com/watch?v=hbmV1bnQ-i0)
        - set of 3 (videos):
            - [Emacs Tutorial (Beginners) -Part 1- File commands, cut/copy/paste, cursor commands](https://www.youtube.com/watch?v=ujODL7MD04Q)
            - [Emacs Tutorial (Beginners) -Part 2- Buffer management, search, M-x grep and rgrep modes](https://www.youtube.com/watch?v=XWpsRupJ4II)
            - [Emacs Tutorial (Beginners) -Part 3- Expressions, Statements, ~/.emacs file and packages](https://www.youtube.com/watch?v=paSgzPso-yc)
        - [Evil Mode: Or, How I Learned to Stop Worrying and Love Emacs (video)](https://www.youtube.com/watch?v=JWD1Fpdd4Pc)
        - [Writing C Programs With Emacs](http://www.cs.yale.edu/homes/aspnes/classes/223/notes.html#Writing_C_programs_with_Emacs)
        - [(maybe) Org Mode In Depth: Managing Structure (video)](https://www.youtube.com/watch?v=nsGYet02bEk)

- ### Unix command line tools
    - I filled in the list below from good tools.
    - bash
    - cat
    - grep
    - sed
    - awk
    - curl or wget
    - sort
    - tr
    - uniq
    - [strace](https://en.wikipedia.org/wiki/Strace)
    - [tcpdump](https://danielmiessler.com/study/tcpdump/)

- ### Information theory (videos)
    - [Khan Academy](https://www.khanacademy.org/computing/computer-science/informationtheory)
    - More about Markov processes:
        - [Core Markov Text Generation](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/waxgx/core-markov-text-generation)
        - [Core Implementing Markov Text Generation](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/gZhiC/core-implementing-markov-text-generation)
        - [Project = Markov Text Generation Walk Through](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/EUjrq/project-markov-text-generation-walk-through)
    - See more in MIT 6.050J Information and Entropy series below

- ### Parity & Hamming Code (videos)
    - [Intro](https://www.youtube.com/watch?v=q-3BctoUpHE)
    - [Parity](https://www.youtube.com/watch?v=DdMcAUlxh1M)
    - Hamming Code:
        - [Error detection](https://www.youtube.com/watch?v=1A_NcXxdoCc)
        - [Error correction](https://www.youtube.com/watch?v=JAMLuxdHH8o)
    - [Error Checking](https://www.youtube.com/watch?v=wbH2VxzmoZk)

- ### Entropy
    - Also see videos below
    - Make sure to watch information theory videos first
    - [Information Theory, Claude Shannon, Entropy, Redundancy, Data Compression & Bits (video)](https://youtu.be/JnJq3Py0dyM?t=176)

- ### Cryptography
    - Also see videos below
    - Make sure to watch information theory videos first
    - [Khan Academy Series](https://www.khanacademy.org/computing/computer-science/cryptography)
    - [Cryptography: Hash Functions](https://www.youtube.com/watch?v=KqqOXndnvic&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=30)
    - [Cryptography: Encryption](https://www.youtube.com/watch?v=9TNI2wHmaeI&index=31&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp)

- ### Compression
    - Make sure to watch information theory videos first
    - Computerphile (videos):
        - [Compression](https://www.youtube.com/watch?v=Lto-ajuqW3w)
        - [Entropy in Compression](https://www.youtube.com/watch?v=M5c_RFKVkko)
        - [Upside Down Trees (Huffman Trees)](https://www.youtube.com/watch?v=umTbivyJoiI)
        - [EXTRA BITS/TRITS - Huffman Trees](https://www.youtube.com/watch?v=DV8efuB3h2g)
        - [Elegant Compression in Text (The LZ 77 Method)](https://www.youtube.com/watch?v=goOa3DGezUA)
        - [Text Compression Meets Probabilities](https://www.youtube.com/watch?v=cCDCfoHTsaU)
    - [Compressor Head videos](https://www.youtube.com/playlist?list=PLOU2XLYxmsIJGErt5rrCqaSGTMyyqNt2H)
    - [(optional) Google Developers Live: GZIP is not enough!](https://www.youtube.com/watch?v=whGwm0Lky2s)

- ### Computer Security
    - [MIT (23 videos)](https://www.youtube.com/playlist?list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)
        - [Introduction, Threat Models](https://www.youtube.com/watch?v=GqmQg-cszw4&index=1&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)
        - [Control Hijacking Attacks](https://www.youtube.com/watch?v=6bwzNg5qQ0o&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh&index=2)
        - [Buffer Overflow Exploits and Defenses](https://www.youtube.com/watch?v=drQyrzRoRiA&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh&index=3)
        - [Privilege Separation](https://www.youtube.com/watch?v=6SIJmoE9L9g&index=4&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)
        - [Capabilities](https://www.youtube.com/watch?v=8VqTSY-11F4&index=5&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)
        - [Sandboxing Native Code](https://www.youtube.com/watch?v=VEV74hwASeU&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh&index=6)
        - [Web Security Model](https://www.youtube.com/watch?v=chkFBigodIw&index=7&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)
        - [Securing Web Applications](https://www.youtube.com/watch?v=EBQIGy1ROLY&index=8&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)
        - [Symbolic Execution](https://www.youtube.com/watch?v=yRVZPvHYHzw&index=9&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)
        - [Network Security](https://www.youtube.com/watch?v=SIEVvk3NVuk&index=11&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)
        - [Network Protocols](https://www.youtube.com/watch?v=QOtA76ga_fY&index=12&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)
        - [Side-Channel Attacks](https://www.youtube.com/watch?v=PuVMkSEcPiI&index=15&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)

- ### Garbage collection
    - [GC in Python (video)](https://www.youtube.com/watch?v=iHVs_HkjdmI)
    - [Deep Dive Java: Garbage Collection is Good!](https://www.infoq.com/presentations/garbage-collection-benefits)
    - [Deep Dive Python: Garbage Collection in CPython (video)](https://www.youtube.com/watch?v=P-8Z0-MhdQs&list=PLdzf4Clw0VbOEWOS_sLhT_9zaiQDrS5AR&index=3)

- ### Parallel Programming
    - [Coursera (Scala)](https://www.coursera.org/learn/parprog1/home/week/1)
    - [Efficient Python for High Performance Parallel Computing (video)](https://www.youtube.com/watch?v=uY85GkaYzBk)

- ### Messaging, Serialization, and Queueing Systems
    - [Thrift](https://thrift.apache.org/)
        - [Tutorial](http://thrift-tutorial.readthedocs.io/en/latest/intro.html)
    - [Protocol Buffers](https://developers.google.com/protocol-buffers/)
        - [Tutorials](https://developers.google.com/protocol-buffers/docs/tutorials)
    - [gRPC](http://www.grpc.io/)
        - [gRPC 101 for Java Developers (video)](https://www.youtube.com/watch?v=5tmPvSe7xXQ&list=PLcTqM9n_dieN0k1nSeN36Z_ppKnvMJoly&index=1)
    - [Redis](http://redis.io/)
        - [Tutorial](http://try.redis.io/)
    - [Amazon SQS (queue)](https://aws.amazon.com/sqs/)
    - [Amazon SNS (pub-sub)](https://aws.amazon.com/sns/)
    - [RabbitMQ](https://www.rabbitmq.com/)
        - [Get Started](https://www.rabbitmq.com/getstarted.html)
    - [Celery](http://www.celeryproject.org/)
        - [First Steps With Celery](http://docs.celeryproject.org/en/latest/getting-started/first-steps-with-celery.html)
    - [ZeroMQ](http://zeromq.org/)
        - [Intro - Read The Manual](http://zeromq.org/intro:read-the-manual)
    - [ActiveMQ](http://activemq.apache.org/)
    - [Kafka](http://kafka.apache.org/documentation.html#introduction)
    - [MessagePack](http://msgpack.org/index.html)
    - [Avro](https://avro.apache.org/)

- ### A*
    - [A Search Algorithm](https://en.wikipedia.org/wiki/A*_search_algorithm)
    - [A* Pathfinding Tutorial (video)](https://www.youtube.com/watch?v=KNXfSOx4eEE)
    - [A* Pathfinding (E01: algorithm explanation) (video)](https://www.youtube.com/watch?v=-L-WgKMFuhE)

- ### Fast Fourier Transform
    - [An Interactive Guide To The Fourier Transform](https://betterexplained.com/articles/an-interactive-guide-to-the-fourier-transform/)
    - [What is a Fourier transform? What is it used for?](http://www.askamathematician.com/2012/09/q-what-is-a-fourier-transform-what-is-it-used-for/)
    - [What is the Fourier Transform? (video)](https://www.youtube.com/watch?v=Xxut2PN-V8Q)
    - [Divide & Conquer: FFT (video)](https://www.youtube.com/watch?v=iTMn0Kt18tg&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=4)
    - [Understanding The FFT](http://jakevdp.github.io/blog/2013/08/28/understanding-the-fft/)

- ### Bloom Filter
    - Given a Bloom filter with m bits and k hashing functions, both insertion and membership testing are O(k)
    - [Bloom Filters (video)](https://www.youtube.com/watch?v=-SuTGoFYjZs)
    - [Bloom Filters | Mining of Massive Datasets | Stanford University (video)](https://www.youtube.com/watch?v=qBTdukbzc78)
    - [Tutorial](http://billmill.org/bloomfilter-tutorial/)
    - [How To Write A Bloom Filter App](http://blog.michaelschmatz.com/2016/04/11/how-to-write-a-bloom-filter-cpp/)

- ### HyperLogLog
    - [How To Count A Billion Distinct Objects Using Only 1.5KB Of Memory](http://highscalability.com/blog/2012/4/5/big-data-counting-how-to-count-a-billion-distinct-objects-us.html)

- ### Locality-Sensitive Hashing
    - Used to determine the similarity of documents
    - The opposite of MD5 or SHA which are used to determine if 2 documents/strings are exactly the same
    - [Simhashing (hopefully) made simple](http://ferd.ca/simhashing-hopefully-made-simple.html)

- ### van Emde Boas Trees
    - [Divide & Conquer: van Emde Boas Trees (video)](https://www.youtube.com/watch?v=hmReJCupbNU&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=6)
    - [MIT Lecture Notes](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-046j-design-and-analysis-of-algorithms-spring-2012/lecture-notes/MIT6_046JS12_lec15.pdf)

- ### Augmented Data Structures
    - [CS 61B Lecture 39: Augmenting Data Structures](https://archive.org/details/ucberkeley_webcast_zksIj9O8_jc)

- ### Balanced search trees
    - Know at least one type of balanced binary tree (and know how it's implemented):
    - "Among balanced search trees, AVL and 2/3 trees are now passé, and red-black trees seem to be more popular.
        A particularly interesting self-organizing data structure is the splay tree, which uses rotations
        to move any accessed key to the root." - Skiena
    - Of these, I chose to implement a splay tree. From what I've read, you won't implement a
        balanced search tree in your interview. But I wanted exposure to coding one up
        and let's face it, splay trees are the bee's knees. I did read a lot of red-black tree code
        - Splay tree: insert, search, delete functions
        If you end up implementing red/black tree try just these:
        - Search and insertion functions, skipping delete
    - I want to learn more about B-Tree since it's used so widely with very large data sets
    - [Self-balancing binary search tree](https://en.wikipedia.org/wiki/Self-balancing_binary_search_tree)

    - **AVL trees**
        - In practice:
            From what I can tell, these aren't used much in practice, but I could see where they would be:
            The AVL tree is another structure supporting O(log n) search, insertion, and removal. It is more rigidly
            balanced than red–black trees, leading to slower insertion and removal but faster retrieval. This makes it
            attractive for data structures that may be built once and loaded without reconstruction, such as language
            dictionaries (or program dictionaries, such as the opcodes of an assembler or interpreter)
        - [MIT AVL Trees / AVL Sort (video)](https://www.youtube.com/watch?v=FNeL18KsWPc&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=6)
        - [AVL Trees (video)](https://www.coursera.org/learn/data-structures/lecture/Qq5E0/avl-trees)
        - [AVL Tree Implementation (video)](https://www.coursera.org/learn/data-structures/lecture/PKEBC/avl-tree-implementation)
        - [Split And Merge](https://www.coursera.org/learn/data-structures/lecture/22BgE/split-and-merge)

    - **Splay trees**
        - In practice:
            Splay trees are typically used in the implementation of caches, memory allocators, routers, garbage collectors,
            data compression, ropes (replacement of string used for long text strings), in Windows NT (in the virtual memory,
            networking and file system code) etc
        - [CS 61B: Splay Trees (video)](https://archive.org/details/ucberkeley_webcast_G5QIXywcJlY)
        - MIT Lecture: Splay Trees:
            - Gets very mathy, but watch the last 10 minutes for sure.
            - [Video](https://www.youtube.com/watch?v=QnPl_Y6EqMo)

    - **Red/black trees**
        - នេះជាការពិពណ៌នាអំពីដេីមឈេី 2-3 (មើលខាងក្រោម).
        - ក្នុងការអនុវត្ត ៖
            Red–black trees ផ្តល់ជូនការធានាករណីអាក្រក់បំផុតសម្រាប់ពេលវេលាបញ្ចូល ពេលវេលាលុប និង ពេលវេលាស្វែងរក។
            វាមិនត្រឹមតែធ្វើឱ្យពួកគេល្អនៅក្នុងកម្មវិធីដែលត្រូវការពេលវេលាប៉ុណ្ណោះទេ ដូចជាកម្មវិធីជាក់ស្តែង
            ប៉ុន្តែវាធ្វើឱ្យពួកគេប្លុកមានតម្លៃនៅក្នុងរចនាសម្ព័ន្ធទិន្នន័យផ្សេងទៀតដែលផ្តល់នូវការធានាករណីអាក្រក់បំផុត។
            ឧទាហរណ៍រចនាសម្ព័ន្ធទិន្នន័យជាច្រើនដែលត្រូវបានប្រើក្នុងធរណីមាត្រគណនាអាចផ្អែកលើដើមឈើ red–black និង Completely Fair Scheduler ដែលប្រើនៅក្នុងខឺណែលលីនុចបច្ចុប្បន្នប្រើដើមឈើred–black ។ 
            នៅក្នុងកំណែ ៨ នៃចាវ៉ា ការប្រមូលHashMapត្រូវបានកែប្រែហើយដើមឈើ Red-Black ត្រូវបានប្រើ ជំនួសឱ្យការប្រើLinkedListដើម្បីផ្ទុកធាតុដូចគ្នាបេះបិទទៅនឹងhashcodes មិនល្អ
        - [Aduni - Algorithms - Lecture 4 (តំណភ្ជាប់លោតទៅចំណុចចាប់ផ្តើម) (វីដេអូ)](https://youtu.be/1W3x0f_RmUo?list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&t=3871)
        - [Aduni - Algorithms - Lecture 5 (វីដេអូ)](https://www.youtube.com/watch?v=hm2GHwyKF1o&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=5)
        - [Red-Black Tree](https://en.wikipedia.org/wiki/Red%E2%80%93black_tree)
        - [An Introduction To Binary Search And Red Black Tree](https://www.topcoder.com/community/competitive-programming/tutorials/an-introduction-to-binary-search-and-red-black-trees/)

    - **2-3 search trees**
        - ក្នុងការអនុវត្ត ៖
            2-3 trees មានការបញ្ចូលលឿនជាងមុននៅក្នុងការចំណាយនៃការស្វែងរកយឺត (ដោយសារកំពស់ខ្ពស់ជាងបេីប្រៀបទៅ AVL trees).
        - អ្នកអាចនឹងកំរប្រេី 2-3 tree ដោយសារតែការអនុវត្តរបស់វាទាក់ទងនឹងប្រភេទផ្សេងៗគ្នានៃថ្នាំង. ជំនួសវិញយេីងប្រេី Red Black trees.
        - [23-Tree Intuition និង និយមន័យ (វីដេអូ)](https://www.youtube.com/watch?v=C3SsdUqasD4&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6&index=2)
        - [Binary View of 23-Tree](https://www.youtube.com/watch?v=iYvBtGKsqSg&index=3&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6)
        - [2-3 Trees (student recitation) (វីដេអូ)](https://www.youtube.com/watch?v=TOb1tuEZ2X4&index=5&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp)

    - **2-3-4 Trees (aka 2-4 trees)**
        - ក្នុងការអនុវត្ត៖
            សម្រាប់រាល់ 2-4 tree, វាមាន red–black trees ជាមួយ data elements ដែលមានលំដាប់ដូចគ្នា. ការបញ្ចូលនិងការលុប
             ប្រតិបត្ដិការនៅលើដើមឈើ 2-4 គឺស្មើទៅនឹងត្រឡប់ពណ៌និងការបង្វិលនៅក្នុងដើមឈើខ្មៅក្រហម. នេះធ្វើឱ្យដើមឈើ 2-4 ដើម
             ឧបករណ៍សំខាន់សម្រាប់ការស្វែងយល់ពីតក្កវិជ្ជានៅពីក្រោយដើមឈើក្រហម - ក្រហមហើយនេះជាមូលហេតុដែលអត្ថបទណែនាំជាច្រើននៃក្បួនដោះស្រាយណែនាំ
             ដើមឈើ ២-៤ ដើមមុនដើមឈើក្រហម - ក្រហមទោះបី ** ដើមឈើ ២-៤ ក៏មិនត្រូវបានប្រើក្នុងការអនុវត្តជាក់ស្តែងដែរ ** ។
        - [CS 61B មេរៀនទី 26: Balanced Search Trees (វីដេអូ)](https://archive.org/details/ucberkeley_webcast_zqrqYXkth6Q)
        - [Bottom Up 234-Trees (វីដេអូ)](https://www.youtube.com/watch?v=DQdMYevEyE4&index=4&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6)
        - [Top Down 234-Trees (វីដេអូ)](https://www.youtube.com/watch?v=2679VQ26Fp4&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6&index=5)

    - **N-ary (K-ary, M-ary) trees**
        - ចំណាំ: the N ឬ K ជា branching factor (max branches)
        - binary trees គឺជា 2-ary tree មួយ, ដែលមាន branching factor = 2
        - 2-3 trees គឺជា 3-ary
        - [K-Ary Tree](https://en.wikipedia.org/wiki/K-ary_tree)

    - **B-Trees**
        - ការពិត: វាជាអាថ៌កំបាំង, តែ B អាចជា Boeing, Balanced, ឬ Bayer (co-inventor).
        - ក្នុងការអនុវត្ត:
            B-Trees ត្រូវបានប្រើយ៉ាងទូលំទូលាយនៅក្នុង databases. filesystems ទំនើបបំផុតភាគច្រេីនប្រេី B-trees (ឬ Variants). បន្ថែមពីលើ
             ការប្រើប្រាស់របស់វានៅក្នុង databases, B-tree ក៏ត្រូវបានប្រើនៅក្នុង filesystems ដើម្បីអនុញ្ញាតឱ្យចូលទៅកាន់ quick random access ទៅ arbitrary
            block មួយ ក្នុងឯកសារជាក់លាក់មួយ. បញ្ហាមូលដ្ឋានគឺការប្រែក្លាយបណ្តុំឯកសារអាយទៅជាប្លុកឌីស (ឬ ប្រហែលជាអាសយដ្ឋាន cylinder-head-sector)
        - [B-Tree](https://en.wikipedia.org/wiki/B-tree)
        - [B-Tree Datastructure](http://btechsmartclass.com/data_structures/b-trees.html)
        - [សេចក្តីផ្តើមទៅ B-Trees (វីដេអូ)](https://www.youtube.com/watch?v=I22wEC1tTGo&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6&index=6)
        - [និយមន័យ B-Tree និង Insertion (វីដេអូ)](https://www.youtube.com/watch?v=s3bCdZGrgpA&index=7&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6)
        - [ការលុប B-Tree (វីដេអូ)](https://www.youtube.com/watch?v=svfnVhJOfMc&index=8&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6)
        - [MIT 6.851 - Memory Hierarchy Models (វីដេអូ)](https://www.youtube.com/watch?v=V3omVLzI0WE&index=7&list=PLUl4u3cNGP61hsJNdULdudlRL493b-XZf)
                - រៀនពី cache-oblivious B-Trees, data structures
                - ៣៧ នាទីដំបូងគឺបច្ចេកទេសហើយប្រហែលជាអាចរំលងចោល (B is block size, cache line size)


- ### k-D Trees
    - ល្អសម្រាប់ការស្វែងរកចំនួនចំនុចក្នុងចតុកោណកែងឬវត្ថុវិមាត្រខ្ពស់
    - ល្អសំរាប់ k-nearest neighbors
    - [Kd Trees (វីដេអូ)](https://www.youtube.com/watch?v=W94M9D_yXKk)
    - [kNN K-d tree algorithm (វីដេអូ)](https://www.youtube.com/watch?v=Y4ZgLlDfKDg)

- ### Skip lists
    - "These are somewhat of a cult data structure" - Skiena
    - [Randomization: Skip Lists (វីដេអូ)](https://www.youtube.com/watch?v=2g9OSRKJuzM&index=10&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp)
    - [សម្រាប់ចលនានិងលម្អិតបន្ថែមទៀត](https://en.wikipedia.org/wiki/Skip_list)

- ### Network Flows
    - [Ford-Fulkerson in 5 minutes — Step by step example (វីដេអូ)](https://www.youtube.com/watch?v=Tl90tNtKvxs)
    - [Ford-Fulkerson Algorithm (វីដេអូ)](https://www.youtube.com/watch?v=v1VgJmkEJW0)
    - [Network Flows (វីដេអូ)](https://www.youtube.com/watch?v=2vhN4Ice5jI)

- ### Disjoint Sets & Union Find
    - [UCB 61B - Disjoint Sets; Sorting & selection (វីដេអូ)](https://archive.org/details/ucberkeley_webcast_MAEGXTwmUsI)
    - [Sedgewick Algorithms - Union-Find (6 videos)](https://www.coursera.org/learn/algorithms-part1/home/week/1)

- ### Math for Fast Processing
    - [Integer Arithmetic, Karatsuba Multiplication (វីដេអូ)](https://www.youtube.com/watch?v=eCaXlAaN2uE&index=11&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb)
    - [The Chinese Remainder Theorem (ប្រេីក្នុង cryptography) (វីដេអូ)](https://www.youtube.com/watch?v=ru7mWZJlRQg)

- ### Treap
    - ការរួមបញ្ចូលគ្នានៃ binary search tree និង a heap
    - [Treap](https://en.wikipedia.org/wiki/Treap)
    - [Data Structures: Treaps explained (វីដេអូ)](https://www.youtube.com/watch?v=6podLUYinH8)
    - [Applications in set operations](https://www.cs.cmu.edu/~scandal/papers/treaps-spaa98.pdf)

- ### Linear Programming (វីដេអូ)
    - [Linear Programming](https://www.youtube.com/watch?v=M4K6HYLHREQ)
    - [Finding minimum cost](https://www.youtube.com/watch?v=2ACJ9ewUC6U)
    - [Finding maximum value](https://www.youtube.com/watch?v=8AA_81xI3ik)
    - [Solve Linear Equations with Python - Simplex Algorithm](https://www.youtube.com/watch?v=44pAWI7v5Zk)

- ### Geometry, Convex hull (វីដេអូ)
    - [Graph Alg. IV: Intro to geometric algorithms - មេរៀនទី 9](https://youtu.be/XIAQRlNkJAw?list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&t=3164)
    - [Geometric Algorithms: Graham & Jarvis - មេរៀនទី 10](https://www.youtube.com/watch?v=J5aJEcOr6Eo&index=10&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm)
    - [Divide & Conquer: Convex Hull, Median Finding](https://www.youtube.com/watch?v=EzeYI7p9MjU&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=2)

- ### Discrete math
    - សូមមើលវីដេអូខាងក្រោម

- ### Machine Learning
    - ហេតុអ្វី ML?
        - [Google ធ្វេីខ្លួនជាក្រុមហ៊ុន Machine Learning ](https://backchannel.com/how-google-is-remaking-itself-as-a-machine-learning-first-company-ada63defcb70)
        - [Large-Scale Deep Learning for Intelligent Computer Systems (វីដេអូ)](https://www.youtube.com/watch?v=QSaZGT4-6EY)
        - [Deep Learning and Understandability versus Software Engineering and Verification ដោយ Peter Norvig](https://www.youtube.com/watch?v=X769cyzBNVw)
    - [Google's Cloud Machine learning tools (វីដេអូ)](https://www.youtube.com/watch?v=Ja2hxBAwG_0)
    - [Google Developers' Machine Learning Recipes (Scikit Learn & Tensorflow) (វីដេអូ)](https://www.youtube.com/playlist?list=PLOU2XLYxmsIIuiBfYad6rFYQU_jL2ryal)
    - [Tensorflow (វីដេអូ)](https://www.youtube.com/watch?v=oZikw5k_2FM)
    - [Tensorflow Tutorials](https://www.tensorflow.org/versions/r0.11/tutorials/index.html)
    - [Practical Guide to implementing Neural Networks in Python (using Theano)](http://www.analyticsvidhya.com/blog/2016/04/neural-networks-python-theano/)
    - វគ្គសិក្សា:
        - [វគ្គចាប់ផ្តើមដ៏អស្ចារ្យ: Machine Learning](https://www.coursera.org/learn/machine-learning)
              - [វីដេអូ](https://www.youtube.com/playlist?list=PLZ9qNFMHZ-A4rycgrgOYma6zxF4BZGGPW)
              - មេីលវីដេអូ 12-18 សំរាប់ linear algebra (14 និង 15 ដូចគ្នា)
        - [Neural Networks for Machine Learning](https://www.coursera.org/learn/neural-networks)
        - [Google's Deep Learning Nanodegree](https://www.udacity.com/course/deep-learning--ud730)
        - [Google/Kaggle Machine Learning Engineer Nanodegree](https://www.udacity.com/course/machine-learning-engineer-nanodegree-by-google--nd009)
        - [Self-Driving Car Engineer Nanodegree](https://www.udacity.com/drive)
        - [Metis Online Course ($99 សំរាប់ 2 ខែ)](http://www.thisismetis.com/explore-data-science)
    - ធនធាន:
        - សៀវភៅ:
            - [Python Machine Learning](https://www.amazon.com/Python-Machine-Learning-Sebastian-Raschka/dp/1783555130/)
            - [Data Science from Scratch: First Principles with Python](https://www.amazon.com/Data-Science-Scratch-Principles-Python/dp/149190142X)
            - [Introduction to Machine Learning with Python](https://www.amazon.com/Introduction-Machine-Learning-Python-Scientists/dp/1449369413/)
        - [Machine Learning សម្រាប់វិស្វករ Software](https://github.com/ZuzooVn/machine-learning-for-software-engineers)
        - Data School: http://www.dataschool.io/

---

## Additional Detail on Some Subjects
## ពត៌មានលំអិតបន្ថែមលើមុខវិជ្ជាមួយចំនួន

    ខ្ញុំបានបន្ថែមគំនិតទាំងនេះដើម្បីពង្រឹងគំនិតមួយចំនួនដែលបានបង្ហាញខាងលើប៉ុន្តែខ្ញុំមិនចង់បញ្ចូលវាខាងលើព្រោះវាច្រើនពេក។ វាងាយស្រួលក្នុងការធ្វើឱ្យវាហួសប្រមាណលើប្រធានបទ។
    អ្នកចង់ទទួលបានការងារនៅសតវត្សនេះមែនទេ? 
    
- **SOLID**   
    - [ ] [Bob Martin SOLID Principles of Object Oriented and Agile Design (វីដេអូ)](https://www.youtube.com/watch?v=TMuno5RZNeE)
    - [ ] S - [Single Responsibility Principle](http://www.oodesign.com/single-responsibility-principle.html) | [Single responsibility to each Object](http://www.javacodegeeks.com/2011/11/solid-single-responsibility-principle.html)
        - [ប្រភេទផ្សេងទៀត](https://docs.google.com/open?id=0ByOwmqah_nuGNHEtcU5OekdDMkk)
    - [ ] O - [Open/Closed Principal](http://www.oodesign.com/open-close-principle.html)  | [On production level Objects are ready for extension but not for modification](https://en.wikipedia.org/wiki/Open/closed_principle)
        - [ប្រភេទផ្សេងទៀត](http://docs.google.com/a/cleancoder.com/viewer?a=v&pid=explorer&chrome=true&srcid=0BwhCYaYDn8EgN2M5MTkwM2EtNWFkZC00ZTI3LWFjZTUtNTFhZGZiYmUzODc1&hl=en)
    - [ ] L - [Liskov Substitution Principal](http://www.oodesign.com/liskov-s-substitution-principle.html) | [Base Class and Derived class follow ‘IS A’ principal](http://stackoverflow.com/questions/56860/what-is-the-liskov-substitution-principle)
        - [ប្រភេទផ្សេងទៀត](http://docs.google.com/a/cleancoder.com/viewer?a=v&pid=explorer&chrome=true&srcid=0BwhCYaYDn8EgNzAzZjA5ZmItNjU3NS00MzQ5LTkwYjMtMDJhNDU5ZTM0MTlh&hl=en)
    - [ ] I - [Interface segregation principle](http://www.oodesign.com/interface-segregation-principle.html) | clients should not be forced to implement interfaces they don't use
        - [គោលការណ៍នៃ Interface Segregation ក្នុងរយៈពេល 5 នាទី (វីដេអូ)](https://www.youtube.com/watch?v=3CtAfl7aXAQ)
        - [ប្រភេទផ្សេងទៀត](http://docs.google.com/a/cleancoder.com/viewer?a=v&pid=explorer&chrome=true&srcid=0BwhCYaYDn8EgOTViYjJhYzMtMzYxMC00MzFjLWJjMzYtOGJiMDc5N2JkYmJi&hl=en)
    - [ ] D -[Dependency Inversion principle](http://www.oodesign.com/dependency-inversion-principle.html) | Reduce the dependency In composition of objects.
        - [ហេតុអ្វីបានជា The Dependency Inversion Principle និងហេតុអ្វីវាសំខាន់](http://stackoverflow.com/questions/62539/what-is-the-dependency-inversion-principle-and-why-is-it-important)
        - [ប្រភេទផ្សេងទៀត](http://docs.google.com/a/cleancoder.com/viewer?a=v&pid=explorer&chrome=true&srcid=0BwhCYaYDn8EgMjdlMWIzNGUtZTQ0NC00ZjQ5LTkwYzQtZjRhMDRlNTQ3ZGMz&hl=en)

- **Union-Find**
    - [Overview](https://www.coursera.org/learn/data-structures/lecture/JssSY/overview)
    - [Naive Implementation](https://www.coursera.org/learn/data-structures/lecture/EM5D0/naive-implementations)
    - [Trees](https://www.coursera.org/learn/data-structures/lecture/Mxu0w/trees)
    - [Union By Rank](https://www.coursera.org/learn/data-structures/lecture/qb4c2/union-by-rank)
    - [Path Compression](https://www.coursera.org/learn/data-structures/lecture/Q9CVI/path-compression)
    - [Analysis Options](https://www.coursera.org/learn/data-structures/lecture/GQQLN/analysis-optional)

- **More Dynamic Programming** (វីដេអូ)
    - [6.006: Dynamic Programming I: Fibonacci, Shortest Paths](https://www.youtube.com/watch?v=OQ5jsbhAv_M&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=19)
    - [6.006: Dynamic Programming II: Text Justification, Blackjack](https://www.youtube.com/watch?v=ENyox7kNKeY&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=20)
    - [6.006: DP III: Parenthesization, Edit Distance, Knapsack](https://www.youtube.com/watch?v=ocZMDMZwhCY&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=21)
    - [6.006: DP IV: Guitar Fingering, Tetris, Super Mario Bros.](https://www.youtube.com/watch?v=tp4_UXaVyx8&index=22&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb)
    - [6.046: Dynamic Programming & Advanced DP](https://www.youtube.com/watch?v=Tw1k46ywN6E&index=14&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp)
    - [6.046: Dynamic Programming: All-Pairs Shortest Paths](https://www.youtube.com/watch?v=NzgFUwOaoIw&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=15)
    - [6.046: Dynamic Programming (student recitation)](https://www.youtube.com/watch?v=krZI60lKPek&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=12)

- **Advanced Graph Processing** (វីដេអូ)
    - [Synchronous Distributed Algorithms: Symmetry-Breaking. Shortest-Paths Spanning Trees](https://www.youtube.com/watch?v=mUBmcbbJNf4&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=27)
    - [Asynchronous Distributed Algorithms: Shortest-Paths Spanning Trees](https://www.youtube.com/watch?v=kQ-UQAzcnzA&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=28)

- MIT **Probability** ប្រូបាប (គណិតវិទ្យា បងៀនយឹតល្អ) (វីដេអូ):
    - [MIT 6.042J - Probability Introduction](https://www.youtube.com/watch?v=SmFwFdESMHI&index=18&list=PLB7540DEDD482705B)
    - [MIT 6.042J - Conditional Probability](https://www.youtube.com/watch?v=E6FbvM-FGZ8&index=19&list=PLB7540DEDD482705B)
    - [MIT 6.042J - Independence](https://www.youtube.com/watch?v=l1BCv3qqW4A&index=20&list=PLB7540DEDD482705B)
    - [MIT 6.042J - Random Variables](https://www.youtube.com/watch?v=MOfhhFaQdjw&list=PLB7540DEDD482705B&index=21)
    - [MIT 6.042J - Expectation I](https://www.youtube.com/watch?v=gGlMSe7uEkA&index=22&list=PLB7540DEDD482705B)
    - [MIT 6.042J - Expectation II](https://www.youtube.com/watch?v=oI9fMUqgfxY&index=23&list=PLB7540DEDD482705B)
    - [MIT 6.042J - Large Deviations](https://www.youtube.com/watch?v=q4mwO2qS2z4&index=24&list=PLB7540DEDD482705B)
    - [MIT 6.042J - Random Walks](https://www.youtube.com/watch?v=56iFMY8QW2k&list=PLB7540DEDD482705B&index=25)

- [Simonson: Approximation Algorithms (video)](https://www.youtube.com/watch?v=oDniZCmNmNw&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=19)

- **String Matching**
    - Rabin-Karp (វីដេអូ):
        - [Rabin Karps Algorithm](https://www.coursera.org/learn/data-structures/lecture/c0Qkw/rabin-karps-algorithm)
        - [Precomputing](https://www.coursera.org/learn/data-structures/lecture/nYrc8/optimization-precomputation)
        - [Optimization: Implementation and Analysis](https://www.coursera.org/learn/data-structures/lecture/h4ZLc/optimization-implementation-and-analysis)
        - [Table Doubling, Karp-Rabin](https://www.youtube.com/watch?v=BRO7mVIFt08&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=9)
        - [Rolling Hashes, Amortized Analysis](https://www.youtube.com/watch?v=w6nuXg0BISo&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=32)
    - Knuth-Morris-Pratt (KMP):
        - [TThe Knuth-Morris-Pratt (KMP) String Matching Algorithm](https://www.youtube.com/watch?v=5i7oKodCRJo)
    - Boyer–Moore string search algorithm
        - [Boyer-Moore String Search Algorithm](https://en.wikipedia.org/wiki/Boyer%E2%80%93Moore_string_search_algorithm)
        - [Advanced String Searching Boyer-Moore-Horspool Algorithms (វីដេអូ)](https://www.youtube.com/watch?v=QDZpzctPf10)
    - [Coursera: Algorithms អំពី Strings](https://www.coursera.org/learn/algorithms-on-strings/home/week/1)
        - ចាប់ផ្តើមល្អ ប៉ុន្តែដល់ពេលហួស KMP វាកាន់តែស្មុគស្មាញ
        - ការពន្យល់ដ៏ល្អនៃការព្យាយាម
        - អាចរំលងបាន

- **Sorting**

    - Stanford lectures on sorting:
        - [មេរៀនទី 15 | Programming Abstractions (វីដេអូ)](https://www.youtube.com/watch?v=ENp00xylP7c&index=15&list=PLFE6E58F856038C69)
        - [មេរៀនទី 16 | Programming Abstractions (វីដេអូ)](https://www.youtube.com/watch?v=y4M9IVgrVKo&index=16&list=PLFE6E58F856038C69)
    - Shai Simonson, [Aduni.org](http://www.aduni.org/):
        - [Algorithms - Sorting - មេរៀនទី 2 (វីដេអូ)](https://www.youtube.com/watch?v=odNJmw5TOEE&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=2)
        - [Algorithms - Sorting II - មេរៀនទី 3 (វីដេអូ)](https://www.youtube.com/watch?v=hj8YKFTFKEE&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=3)
    - ការបង្រៀនរបស់ Steven Skiena អំពី sorting:
        - [មេរៀនចាប់ផ្តេីមពី 26:46 (វីដេអូ)](https://youtu.be/ute-pmMkyuk?list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&t=1600)
        - [មេរៀនចាប់ផ្តេីមពី 27:40 (វីដេអូ)](https://www.youtube.com/watch?v=yLvp-pB8mak&index=8&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b)
        - [មេរៀនចាប់ផ្តេីមពី 35:00 (វីដេអូ)](https://www.youtube.com/watch?v=q7K9otnzlfE&index=9&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b)
        - [មេរៀនចាប់ផ្តេីមពី 23:50 (វីដេអូ)](https://www.youtube.com/watch?v=TvqIGu9Iupw&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=10)

## Video Series
## ស៊េរីវីដេអូ

រីករាយជាមួយវិដេអូរខាងក្រោម

- [List of individual Dynamic Programming problems (each is short)](https://www.youtube.com/playlist?list=PLrmLmBdmIlpsHaNTPP_jHHDx_os9ItYXr)

- [x86 Architecture, Assembly, Applications (11 វីដេអូ)](https://www.youtube.com/playlist?list=PL038BE01D3BAEFDB0)

- [MIT 18.06 Linear Algebra, Spring 2005 (35 វីដេអូ)](https://www.youtube.com/playlist?list=PLE7DDD91010BC51F8)

- [Excellent - MIT Calculus Revisited: Single Variable Calculus](https://www.youtube.com/playlist?list=PL3B08AE665AB9002A)

- [Computer Science 70, 001 - Spring 2015 - Discrete Mathematics and Probability Theory](http://www.infocobuild.com/education/audio-video-courses/computer-science/cs70-spring2015-berkeley.html)

- [Discrete Mathematics ដោយ Shai Simonson (19 វីដេអូ)](https://www.youtube.com/playlist?list=PL3o9D4Dl2FJ9q0_gtFXPh_H4POI5dK0yG)

- [Discrete Mathematics Part 1 by Sarada Herke (5 វីដេអូ)](https://www.youtube.com/playlist?list=PLGxuz-nmYlQPOc4w1Kp2MZrdqOOm4Jxeo)

- CSE373 - Analysis of Algorithms (25 វីដេអូ)
    - [ការបង្រៀនរបស់ Skiena ពី Algorithm Design Manual](https://www.youtube.com/watch?v=ZFjhkohHdAA&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=1)

- [UC Berkeley 61B (Spring 2014): Data Structures (25 វីដេអូ)](https://archive.org/details/ucberkeley-webcast-PL-XXv-cvA_iAlnI-BQr9hjqADPBtujFJd)

- [UC Berkeley 61B (Fall 2006): Data Structures (39 វីដេអូ)](https://archive.org/details/ucberkeley-webcast-PL4BBB74C7D2A1049C)

- [UC Berkeley 61C: Machine Structures (26 វីដេអូ)](https://archive.org/details/ucberkeley-webcast-PL-XXv-cvA_iCl2-D-FS5mk0jFF6cYSJs_)

- [OOSE: Software Dev Using UML and Java (21 វីដេអូ)](https://www.youtube.com/playlist?list=PLJ9pm_Rc9HesnkwKlal_buSIHA-jTZMpO)

- ~~[UC Berkeley CS 152: Computer Architecture and Engineering (20 videos)](https://www.youtube.com/watch?v=UH0QYvtP7Rk&index=20&list=PLkFD6_40KJIwEiwQx1dACXwh-2Fuo32qr)~~

- [MIT 6.004: Computation Structures (49 វីដេអូ)](https://www.youtube.com/playlist?list=PLDSlqjcPpoL64CJdF0Qee5oWqGS6we_Yu)

- [Carnegie Mellon - Computer Architecture Lectures (39 វីដេអូ)](https://www.youtube.com/playlist?list=PL5PHm2jkkXmi5CxxI7b3JCL1TWybTDtKq)

- [MIT 6.006: Intro to Algorithms (47 វីដេអូ)](https://www.youtube.com/watch?v=HtSuA80QTyo&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&nohtml5=False)

- [MIT 6.033: Computer System Engineering (22 វីដេអូ)](https://www.youtube.com/watch?v=zm2VP0kHl1M&list=PL6535748F59DCA484)

- [MIT 6.034 Artificial Intelligence, Fall 2010 (30 វីដេអូ)](https://www.youtube.com/playlist?list=PLUl4u3cNGP63gFHB6xb-kVBiQHYe_4hSi)

- [MIT 6.042J: Mathematics for Computer Science, Fall 2010 (25 វីដេអូ)](https://www.youtube.com/watch?v=L3LMbpZIKhQ&list=PLB7540DEDD482705B)

- [MIT 6.046: Design and Analysis of Algorithms (34 វីដេអូ)](https://www.youtube.com/watch?v=2P-yW7LQr08&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp)

- [MIT 6.050J: Information and Entropy, Spring 2008 (19 វីដេអូ)](https://www.youtube.com/watch?v=phxsQrZQupo&list=PL_2Bwul6T-A7OldmhGODImZL8KEVE38X7)

- [MIT 6.851: Advanced Data Structures (22 វីដេអូ)](https://www.youtube.com/watch?v=T0yzrZL1py0&list=PLUl4u3cNGP61hsJNdULdudlRL493b-XZf&index=1)

- [MIT 6.854: Advanced Algorithms, Spring 2016 (24 វីដេអូ)](https://www.youtube.com/playlist?list=PL6ogFv-ieghdoGKGg2Bik3Gl1glBTEu8c)

- [Harvard COMPSCI 224: Advanced Algorithms (25 វីដេអូ)](https://www.youtube.com/playlist?list=PL2SOU6wwxB0uP4rJgf5ayhHWgw7akUWSf)

- [MIT 6.858 Computer Systems Security, Fall 2014](https://www.youtube.com/watch?v=GqmQg-cszw4&index=1&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)

- [Stanford: Programming Paradigms (27 វីដេអូ)](https://www.youtube.com/view_play_list?p=9D558D49CA734A02)

- [Introduction to Cryptography by Christof Paar](https://www.youtube.com/playlist?list=PL6N5qY2nvvJE8X75VkXglSrVhLv1tVcfy)
    - [Course Website along with Slides and Problem Sets](http://www.crypto-textbook.com/)

- [Mining Massive Datasets - Stanford University (94 វីដេអូ)](https://www.youtube.com/playlist?list=PLLssT5z_DsK9JDLcT8T62VtzwyW9LNepV)

- [Graph Theory by Sarada Herke (67 វីដេអូ)](https://www.youtube.com/user/DrSaradaHerke/playlists?shelf_id=5&view=50&sort=dd)

## Computer Science Courses
## វគ្គសិក្សាវិទ្យាសាស្ត្រកុំព្យូទ័រ

- [Directory of Online CS Courses](https://github.com/open-source-society/computer-science)
- [Directory of CS Courses (ភាគច្រើនជាមួយការបង្រៀនតាមអ៊ិនធរណេត)](https://github.com/prakhar1989/awesome-courses)

## Papers
## អត្ថបទ

- [Love classic papers?](https://www.cs.cmu.edu/~crary/819-f09/)
- [1978: Communicating Sequential Processes](http://spinroot.com/courses/summer/Papers/hoare_1978.pdf)
    - [implemented in Go](https://godoc.org/github.com/thomas11/csp)
- [2003: The Google File System](http://static.googleusercontent.com/media/research.google.com/en//archive/gfs-sosp2003.pdf)
    - ជំនួសដោយ Colossus ក្នុងឆ្នាំ 2012
- [2004: MapReduce: Simplified Data Processing on Large Clusters]( http://static.googleusercontent.com/media/research.google.com/en//archive/mapreduce-osdi04.pdf)
    - ជំនួសដោយ Cloud Dataflow?
- [2006: Bigtable: A Distributed Storage System for Structured Data](https://static.googleusercontent.com/media/research.google.com/en//archive/bigtable-osdi06.pdf)
    - [An Inside Look at Google BigQuery](https://cloud.google.com/files/BigQueryTechnicalWP.pdf)
- [2006: The Chubby Lock Service for Loosely-Coupled Distributed Systems](https://research.google.com/archive/chubby-osdi06.pdf)
- [2007: Dynamo: Amazon’s Highly Available Key-value Store](http://s3.amazonaws.com/AllThingsDistributed/sosp/amazon-dynamo-sosp2007.pdf)
    - អត្ថបទ Dynamo ចាប់ផ្តេីមអោយមាន NoSQL 
- [2007: What Every Programmer Should Know About Memory (very long, and the author encourages skipping of some sections)](https://www.akkadia.org/drepper/cpumemory.pdf)
- [2010: Dapper, a Large-Scale Distributed Systems Tracing Infrastructure](https://research.google.com/pubs/archive/36356.pdf)
- [2010: Dremel: Interactive Analysis of Web-Scale Datasets](https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/36632.pdf)
- [2012: Google's Colossus](https://www.wired.com/2012/07/google-colossus/)
    - មិនមាន អត្ថបទ
- 2012: AddressSanitizer: A Fast Address Sanity Checker:
    - [អត្ថបទ](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/37752.pdf)
    - [វីដេអូ](https://www.usenix.org/conference/atc12/technical-sessions/presentation/serebryany)
- 2013: Spanner: Google’s Globally-Distributed Database:
    - [អត្ថបទ](http://static.googleusercontent.com/media/research.google.com/en//archive/spanner-osdi2012.pdf)
    - [វីដេអូ](https://www.usenix.org/node/170855)
- [2014: Machine Learning: The High-Interest Credit Card of Technical Debt](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/43146.pdf)
- [2015: Continuous Pipelines at Google](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/43790.pdf)
- [2015: High-Availability at Massive Scale: Building Google’s Data Infrastructure for Ads](https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/44686.pdf)
- [2015: TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems](http://download.tensorflow.org/paper/whitepaper2015.pdf )
- [2015: How Developers Search for Code: A Case Study](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/43835.pdf)
- [2016: Borg, Omega, and Kubernetes](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/44843.pdf)


## LICENSE
## សាលាកប័រត

[CC-BY-SA-4.0](./LICENSE.txt)
