Clarification on languages.

This commit is contained in:
John Washam 2016-08-01 15:45:42 -07:00
parent 50421305af
commit ed91fa30b6

View File

@ -94,12 +94,14 @@ from public sources and replacing the online course videos over time. I like usi
This short section were prerequisites/interesting info I wanted to learn before getting started on the daily plan.
You need to know C, C++, or Java to do the coding part of the interview.
They will sometimes make an exception and let you use Python or some other language, but the language
must be mainstream and allow you write your code low-level enough to solve the problems.
You'll see some C, C++ learning included below.
You can use a language you are comfortable in to do the coding part of the interview, but for Google, these are solid choices:
- C++
- Java
- Python
You need to be very comfortable in the language, and be knowledgeable. Read more (rescued from the lost web):
- https://web.archive.org/web/20160204193730/http://blog.codingforinterviews.com/best-programming-language-jobs/
There are a few books involved, see the bottom.
You'll see some C, C++, and Python learning included below, because I'm learning. There are a few books involved, see the bottom.
- [x] **How computers process a program:**
- [x] https://www.youtube.com/watch?v=42KTvGYQYnA
@ -678,7 +680,7 @@ Graphs can be used to represent many problems in computer science, so this secti
- I'll implement:
- [x] DFS with adjacency list (recursive)
- [ ] DFS with adjacency matrix (iterative with stack)
- [ ] BFS with adjacency list
- [x] BFS with adjacency list
- [ ] BFS with adjacency matrix
- [x] single-source shortest path (Dijkstra)
- DFS-based algorithms (see Aduni videos above):
@ -937,39 +939,40 @@ You'll get more graph practice in Skiena's book (see Books section below) and th
## Articles
- https://www.topcoder.com/community/data-science/data-science-tutorials/the-importance-of-algorithms/
- http://highscalability.com/blog/2016/4/4/how-to-remove-duplicates-in-a-large-dataset-reducing-memory.html
- http://highscalability.com/blog/2016/3/23/what-does-etsys-architecture-look-like-today.html
- http://highscalability.com/blog/2016/3/21/to-compress-or-not-to-compress-that-was-ubers-question.html
- http://highscalability.com/blog/2016/3/3/asyncio-tarantool-queue-get-in-the-queue.html
- http://highscalability.com/blog/2016/2/25/when-should-approximate-query-processing-be-used.html
- http://highscalability.com/blog/2016/2/23/googles-transition-from-single-datacenter-to-failover-to-a-n.html
- http://highscalability.com/blog/2016/2/15/egnyte-architecture-lessons-learned-in-building-and-scaling.html
- http://highscalability.com/blog/2016/2/1/a-patreon-architecture-short.html
- http://highscalability.com/blog/2016/1/27/tinder-how-does-one-of-the-largest-recommendation-engines-de.html
- http://highscalability.com/blog/2016/1/25/design-of-a-modern-cache.html
- http://highscalability.com/blog/2016/1/13/live-video-streaming-at-facebook-scale.html
- http://highscalability.com/blog/2016/1/11/a-beginners-guide-to-scaling-to-11-million-users-on-amazons.html
- http://highscalability.com/blog/2015/12/16/how-does-the-use-of-docker-effect-latency.html
- http://highscalability.com/blog/2015/12/14/does-amp-counter-an-existential-threat-to-google.html
- http://highscalability.com/blog/2015/11/9/a-360-degree-view-of-the-entire-netflix-stack.html
- http://highscalability.com/latency-everywhere-and-it-costs-you-sales-how-crush-it
- [ ] https://www.topcoder.com/community/data-science/data-science-tutorials/the-importance-of-algorithms/
- [ ] http://highscalability.com/blog/2012/3/26/7-years-of-youtube-scalability-lessons-in-30-minutes.html
- [ ] http://highscalability.com/blog/2016/4/4/how-to-remove-duplicates-in-a-large-dataset-reducing-memory.html
- [ ] http://highscalability.com/blog/2016/3/23/what-does-etsys-architecture-look-like-today.html
- [ ] http://highscalability.com/blog/2016/3/21/to-compress-or-not-to-compress-that-was-ubers-question.html
- [ ] http://highscalability.com/blog/2016/3/3/asyncio-tarantool-queue-get-in-the-queue.html
- [ ] http://highscalability.com/blog/2016/2/25/when-should-approximate-query-processing-be-used.html
- [ ] http://highscalability.com/blog/2016/2/23/googles-transition-from-single-datacenter-to-failover-to-a-n.html
- [ ] http://highscalability.com/blog/2016/2/15/egnyte-architecture-lessons-learned-in-building-and-scaling.html
- [ ] http://highscalability.com/blog/2016/2/1/a-patreon-architecture-short.html
- [ ] http://highscalability.com/blog/2016/1/27/tinder-how-does-one-of-the-largest-recommendation-engines-de.html
- [ ] http://highscalability.com/blog/2016/1/25/design-of-a-modern-cache.html
- [ ] http://highscalability.com/blog/2016/1/13/live-video-streaming-at-facebook-scale.html
- [ ] http://highscalability.com/blog/2016/1/11/a-beginners-guide-to-scaling-to-11-million-users-on-amazons.html
- [ ] http://highscalability.com/blog/2015/12/16/how-does-the-use-of-docker-effect-latency.html
- [ ] http://highscalability.com/blog/2015/12/14/does-amp-counter-an-existential-threat-to-google.html
- [ ] http://highscalability.com/blog/2015/11/9/a-360-degree-view-of-the-entire-netflix-stack.html
- [ ] http://highscalability.com/latency-everywhere-and-it-costs-you-sales-how-crush-it
## Papers:
Computing Weak Consistency in Polynomial Time
- [ ] Computing Weak Consistency in Polynomial Time
- http://dl.acm.org/ft_gateway.cfm?id=2767407&ftid=1607485&dwn=1&CFID=627637486&CFTOKEN=49290244
How Developers Search for Code: A Case Study
- [ ] How Developers Search for Code: A Case Study
- http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/43835.pdf
Borg, Omega, and Kubernetes
- [ ] Borg, Omega, and Kubernetes
- http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/44843.pdf
Continuous Pipelines at Google
- [ ] Continuous Pipelines at Google
- http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/43790.pdf
AddressSanitizer: A Fast Address Sanity Checker
- [ ] AddressSanitizer: A Fast Address Sanity Checker
- http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/37752.pdf
## Coding exercises/challenges: