Added clang, gdb, valgrind.
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John Washam
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plan.txt
53
plan.txt
@ -61,6 +61,11 @@ Some videos are available only by enrolling in a Coursera or EdX class. It is fr
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* - C
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* - K&R C book (ANSI C)
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* - Clang: https://www.youtube.com/watch?v=U3zCxnj2w8M
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* - GDB:
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- https://www.youtube.com/watch?v=USPvePv1uzE
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- https://www.youtube.com/watch?v=y5JmQItfFck
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- Valgrind: https://www.youtube.com/watch?v=fvTsFjDuag8
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- C++
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* - basics
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* - pointers
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@ -136,16 +141,23 @@ Then test it out on a computer to make sure it's not buggy from syntax.
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Arrays
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* - Description:
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- Arrays: https://www.coursera.org/learn/data-structures/lecture/OsBSF/arrays
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- Arrays: https://www.lynda.com/Developer-Programming-Foundations-tutorials/Basic-arrays/149042/177104-4.html
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- Multi-dim: https://www.lynda.com/Developer-Programming-Foundations-tutorials/Multidimensional-arrays/149042/177105-4.html
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- Dynamic Arrays: https://www.coursera.org/learn/data-structures/lecture/EwbnV/dynamic-arrays
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- Resizing arrays: https://class.coursera.org/algs4partI-010/lecture/19
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- Implement:
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- Jagged: https://www.lynda.com/Developer-Programming-Foundations-tutorials/Jagged-arrays/149042/177106-4.html
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- Resizing arrays:
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- https://class.coursera.org/algs4partI-010/lecture/19
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- https://www.lynda.com/Developer-Programming-Foundations-tutorials/Resizable-arrays/149042/177108-4.html
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- Implement a vector (mutable array with automatic resizing):
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* - Practice coding using arrays and pointers, and pointer math to jump to an index instead of using indexing.
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* - new raw data array with allocated memory (can allocate int array under the hood, just not use its features)
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* - new raw data array with allocated memory
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- can allocate int array under the hood, just not use its features
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- start with 16, or if starting number is greater, use power of 2 - 16, 32, 64, 128
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* - size() - number of items
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* - capacity() - number of items it can hold
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* - is_empty()
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- at(index) - returns item at given index
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- append(item) - or push(item)
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- at(index) - returns item at given index, blows up if index out of bounds
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- append(item) - or push(item) - check size of element 2^
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- insert(index, item)
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- prepend(item) - can use insert above at index 0
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- delete(index)
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@ -159,8 +171,8 @@ Arrays
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- O(n) to insert/remove elsewhere
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- Space
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- contiguous in memory, so proximity helps performance
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- space needed = size of object * number of items to store
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linked lists
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- space needed = (array capacity, which is >= n) * size of item
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Linked lists
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- singly-linked
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* - Description: https://www.coursera.org/learn/data-structures/lecture/kHhgK/singly-linked-lists
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* - Lynda.com:
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@ -188,14 +200,13 @@ linked lists
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- doubly-linked list
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- Description: https://www.coursera.org/learn/data-structures/lecture/jpGKD/doubly-linked-lists
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- reverse a singly-linked list
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stacks
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Stacks
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- see: https://class.coursera.org/algs4partI-010/lecture
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- https://www.coursera.org/learn/data-structures/lecture/UdKzQ/stacks
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queues
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Queues
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- see: https://class.coursera.org/algs4partI-010/lecture
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- https://www.coursera.org/learn/data-structures/lecture/EShpq/queues
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Vectors
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heaps
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Heaps
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- https://www.coursera.org/learn/data-structures/lecture/GRV2q/binary-trees
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- min heap
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- max heap
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@ -207,14 +218,14 @@ Priority Queue
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Disjoint Sets:
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- https://www.coursera.org/learn/data-structures/lecture/JssSY/overview
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- https://www.coursera.org/learn/data-structures/lecture/Mxu0w/trees
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hashtables
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Hash tables
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- https://www.youtube.com/watch?v=C4Kc8xzcA68
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- https://class.coursera.org/algs4partI-010/lecture/52
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- https://www.coursera.org/learn/data-structures/home/week/3
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- see: https://class.coursera.org/algs4partI-010/lecture
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- https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/m7UuP/core-hash-tables
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- test: implement with only arrays
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tries
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Tries
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- https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/08Xyf/core-introduction-to-tries
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Circular buffer/FIFO:
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- https://en.wikipedia.org/wiki/Circular_buffer
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@ -231,14 +242,18 @@ Bit operations
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https://www.youtube.com/watch?v=JAMLuxdHH8o
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Error Checking:
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https://www.youtube.com/watch?v=wbH2VxzmoZk
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binary search
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Binary search
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Sorting
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- no bubble sort - it's terrible
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- at least one n*log(n) sorting algorithm, preferably two (say, quicksort and merge sort)
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- Which algorithms can be used on lists? Which on arrays? Which on both? Is Quicksort stable?
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- algos:
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- stability in sorting algorithms:
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- http://stackoverflow.com/questions/1517793/stability-in-sorting-algorithms
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- http://www.geeksforgeeks.org/stability-in-sorting-algorithms/
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- Which algorithms can be used on linked lists? Which on arrays? Which on both? Is Quicksort stable?
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- Implement & know best case/worst case, average complexity of each:
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- mergesort
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- quicksort
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- insertion sort
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- selection sort
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- no bubble sort - it's terrible at O(n^2)
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Caches
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- LRU cache
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Trees
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@ -293,6 +308,8 @@ open-ended problems
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- manipulate strings
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- manipulate patterns
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design patterns:
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- description:
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- https://www.lynda.com/Developer-Programming-Foundations-tutorials/Foundations-Programming-Design-Patterns/135365-2.html
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- strategy
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- singleton
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- adapter
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