coding-interview-university/README.md

# Google Interview University
*(formerly known as Project 9894)*

### What is it?

This is my multi-month study plan for going from web developer (self-taught, no CS degree) to
Google software engineer. Don't let that offend you if you are a web developer. I'm speaking
from my experience, not yours.

    This long list has been extracted and expanded from Google's coaching notes, so these are the things
    you need to know. There are extras at the bottom, but this is the list. No shortcuts.

## Why use it?

I'm following this plan to prepare for my Google interview. I've been building the web, building
services, and launching startups since 1997. I have an economics degree, not a CS degree.  I've
been very successful in my career, but I want to work at Google. I want to progress into larger systems
and get a real understanding of computer systems, algorithmic efficiency, data structure performance,
low-level languages, and how it all works. And if you don't know any of it, Google won't hire you.

When I started this I didn't know a stack from a heap, didn't know Big-O anything, anything about trees, or how to
traverse a graph. If I had to code a sorting algorithm, I can tell ya it wouldn't have been very good.
Every data structure I've ever used was built in to the language, and I didn't know how they worked
under the hood at all. I've never had to manage memory, unless a process I was running would give an "out of
memory" error, and then I'd have to find a workaround. I've used a few multi-dimensional arrays in my life and
thousands of associative arrays, but I've never created data structures from scratch.

But after going through this study plan I have high confidence I'll be hired. It's a long plan. It's going to take me
months. If you are familiar with a lot of this already it will take you a lot less time.

### How to use it

Everything below is an outline, and you should tackle the items in order from top to bottom.

I'm using Github's special markdown flavor, including tasks lists to check my progress.

I check each task box at the beginning of a line when I'm done with it. When all sub-items in a block are done,
I put [x] at the top level, meaning the entire block is done. Sorry you have to remove all my [x] markings
to use this the same way. If you search/replace, just replace [x] with [ ].
Sometimes I just put a [x] at top level if I know I've done all the subtasks, to cut down on clutter.

More about Github flavored markdown: https://guides.github.com/features/mastering-markdown/#GitHub-flavored-markdown

    I have a friendly referral already to get my resume in at Google. Thanks JP.

## Get in a Googley Mood

Print out a "[future Googler](https://github.com/jwasham/project-9894/blob/master/future-googler.pdf)" sign (or two) and keep your eyes on the prize.

## Interview Process & General Interview Prep

- [x] Videos:
    - [x] https://www.youtube.com/watch?v=oWbUtlUhwa8&feature=youtu.be
    - [x] https://www.youtube.com/watch?v=qc1owf2-220&feature=youtu.be
    - [x] https://www.youtube.com/watch?v=8npJLXkcmu8

- [x] Articles:
    - [x] http://www.google.com/about/careers/lifeatgoogle/hiringprocess/
    - [x] http://steve-yegge.blogspot.com/2008/03/get-that-job-at-google.html
        - all the things he mentions that you need to know are listed below
    - [x] (very dated) http://dondodge.typepad.com/the_next_big_thing/2010/09/how-to-get-a-job-at-google-interview-questions-hiring-process.html
    - [x] http://sites.google.com/site/steveyegge2/five-essential-phone-screen-questions

- [x] Additional (not suggested by Google but I added):
    - [x] https://medium.com/always-be-coding/abc-always-be-coding-d5f8051afce2#.4heg8zvm4
    - [x] https://medium.com/always-be-coding/four-steps-to-google-without-a-degree-8f381aa6bd5e#.asalo1vfx
    - [x] https://medium.com/@dpup/whiteboarding-4df873dbba2e#.hf6jn45g1
    - [x] http://www.kpcb.com/blog/lessons-learned-how-google-thinks-about-hiring-management-and-culture
    - [x] http://www.coderust.com/blog/2014/04/10/effective-whiteboarding-during-programming-interviews/
    - [x] Cracking The Coding Interview Set 1:
        - [x] https://www.youtube.com/watch?v=rEJzOhC5ZtQ
        - [x] https://www.youtube.com/watch?v=aClxtDcdpsQ
    - [x] How to Get a Job at the Big 4:
        - [x] https://www.youtube.com/watch?v=YJZCUhxNCv8
    - [x] http://alexbowe.com/failing-at-google-interviews/


## Prerequisite Knowledge

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.

There are a few books involved, see the bottom.

Some videos are available only by enrolling in a Coursera or EdX class. It is free to do so.

- [x] **How computers process a program:**
    - [x] https://www.youtube.com/watch?v=42KTvGYQYnA
    - [x] https://www.youtube.com/watch?v=Mv2XQgpbTNE

- [x] **How floating point numbers are stored:**
    - [x] simple 8-bit: http://math.stackexchange.com/questions/301435/fractions-in-binary
    - [x] 32 bit: https://www.youtube.com/watch?v=ji3SfClm8TU
    - [x] 64 bit: https://www.youtube.com/watch?v=50ZYcZebIec

- [x] **Computer Arch Intro:**
    (first video only - interesting but not required) https://www.youtube.com/watch?v=zLP_X4wyHbY&list=PL5PHm2jkkXmi5CxxI7b3JCL1TWybTDtKq&index=1

- [x] **C**
    - [x] K&R C book (ANSI C)
    - [x] Clang: https://www.youtube.com/watch?v=U3zCxnj2w8M
    - [x] GDB:
        - https://www.youtube.com/watch?v=USPvePv1uzE
        - https://www.youtube.com/watch?v=y5JmQItfFck
      - Valgrind: https://www.youtube.com/watch?v=fvTsFjDuag8
- [x] **C++**
    - [x] basics
    - [x] pointers
    - [x] functions
    - [x] references
    - [x] templates
    - [x] compilation
    - [x] scope & linkage
    - [x] namespaces
    - [x] OOP
    - [x] STL
    - [x] functors: http://www.cprogramming.com/tutorial/functors-function-objects-in-c++.html
    - [x] C++ at Google: https://www.youtube.com/watch?v=NOCElcMcFik
    - [x] Google C++ Style Guide: https://google.github.io/styleguide/cppguide.html
        - [x] Google uses clang-format (there is a command line "style" argument: -style=google)
    - [x] Efficiency with Algorithms, Performance with Data Structures: https://youtu.be/fHNmRkzxHWs
    - [x] review of C++ concepts: https://www.youtube.com/watch?v=Rub-JsjMhWY

- **Python**
    - I've already use Python quite a bit. This is just for review.
    - [ ] https://www.youtube.com/watch?v=N4mEzFDjqtA

- [x] **Compilers**
    - [x] https://class.coursera.org/compilers-004/lecture/1
    - [x] https://class.coursera.org/compilers-004/lecture/2
    - [x] C++: https://www.youtube.com/watch?v=twodd1KFfGk
    - [x] Understanding Compiler Optimization (C++): https://www.youtube.com/watch?v=FnGCDLhaxKU


## The Daily Plan:

Each subject does not require a whole day to be able to understand it fully, and you can do multiple of these in a day.

Each day I take one subject from the list below, watch videos about that subject, and write an implementation in:
    C - using structs and functions that take a struct * and something else as args.
    C++ - without using built-in types
    C++ - using built-in types, like STL's std::list for a linked list
    Python - using built-in types (to keep practicing Python)
    and write tests to ensure I'm doing it right, sometimes just using simple assert() statements
    You may do Java or something else, this is just my thing.

Why code in all of these?
    Practice, practice, practice, until I'm sick of it, and can do it with no problem (some have many edge cases and bookkeeping details to remember)
    Work within the raw constraints (allocating/freeing memory without help of garbage collection (except Python))
    Make use of built-in types so I have experience using the built-in tools for real-world use (not going to write my own linked list implementation in production)

I may not have time to do all of these for every subject, but I'll try.

You don't need to memorize the guts of every algorithm.

Write code on a whiteboard, not a computer. Test with some sample inputs.
Then test it out on a computer to make sure it's not buggy from syntax.


- [x] **Before you get started:**
    - The myth of the Genius Programmer: https://www.youtube.com/watch?v=0SARbwvhupQ
    - Google engineers are smart, but many have an insecurity that they aren't smart enough.

- [x] **Algorithmic complexity / Big O / Asymptotic analysis**
    - nothing to implement
    - Harvard CS50 - Asymptotic Notation: https://www.youtube.com/watch?v=iOq5kSKqeR4
    - Big O Notations (general quick tutorial) - https://www.youtube.com/watch?v=V6mKVRU1evU
    - Big O Notation (and Omega and Theta) - best mathematical explanation:
        - https://www.youtube.com/watch?v=ei-A_wy5Yxw&index=2&list=PL1BaGV1cIH4UhkL8a9bJGG356covJ76qN
    - Skiena:
        - video: https://www.youtube.com/watch?v=gSyDMtdPNpU&index=2&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b
        - slides: http://www3.cs.stonybrook.edu/~algorith/video-lectures/2007/lecture2.pdf
    - A Gentle Introduction to Algorithm Complexity Analysis: http://discrete.gr/complexity/
    - Orders of Growth: https://class.coursera.org/algorithmicthink1-004/lecture/59
    - Asymptotics: https://class.coursera.org/algorithmicthink1-004/lecture/61
    - UC Berkeley Big O: https://youtu.be/VIS4YDpuP98
    - UC Berkeley Big Omega: https://youtu.be/ca3e7UVmeUc
    - Amortized Analysis: https://www.youtube.com/watch?v=B3SpQZaAZP4&index=10&list=PL1BaGV1cIH4UhkL8a9bJGG356covJ76qN
    - Illustrating "Big O": https://class.coursera.org/algorithmicthink1-004/lecture/63
    - Cheat sheet: http://bigocheatsheet.com/

## Data Structures

- [x] **Arrays: (Implement an automatically resizing vector)**
    - [x] Description:
        - Arrays: https://www.coursera.org/learn/data-structures/lecture/OsBSF/arrays
        - Arrays: https://www.lynda.com/Developer-Programming-Foundations-tutorials/Basic-arrays/149042/177104-4.html
        - Multi-dim: https://www.lynda.com/Developer-Programming-Foundations-tutorials/Multidimensional-arrays/149042/177105-4.html
        - Dynamic Arrays: https://www.coursera.org/learn/data-structures/lecture/EwbnV/dynamic-arrays
        - Jagged: https://www.lynda.com/Developer-Programming-Foundations-tutorials/Jagged-arrays/149042/177106-4.html
        - Resizing arrays:
            - https://class.coursera.org/algs4partI-010/lecture/19
            - https://www.lynda.com/Developer-Programming-Foundations-tutorials/Resizable-arrays/149042/177108-4.html
    - [x] Implement a vector (mutable array with automatic resizing):
        - [x] Practice coding using arrays and pointers, and pointer math to jump to an index instead of using indexing.
        - [x] new raw data array with allocated memory
            - can allocate int array under the hood, just not use its features
            - start with 16, or if starting number is greater, use power of 2 - 16, 32, 64, 128
        - [x] size() - number of items
        - [x] capacity() - number of items it can hold
        - [x] is_empty()
        - [x] at(index) - returns item at given index, blows up if index out of bounds
        - [x] push(item)
        - [x] insert(index, item) - inserts item at index, shifts that index's value and trailing elements to the right
        - [x] prepend(item) - can use insert above at index 0
        - [x] pop() - remove from end, return value
        - [x] delete(index) - delete item at index, shifting all trailing elements left
        - [x] remove(item) - looks for value and removes index holding it (even if in multiple places)
        - [x] find(item) - looks for value and returns first index with that value, -1 if not found
        - [x] resize(new_capacity) // private function
            - when you reach capacity, resize to double the size
            - when popping an item, if size is 1/4 of capacity, resize to half
    - [x] Time
        - O(1) to add/remove at end (amortized for allocations for more space), index, or update
        - O(n) to insert/remove elsewhere
    - [x] Space
        - contiguous in memory, so proximity helps performance
        - space needed = (array capacity, which is >= n) * size of item, but even if 2n, still O(n)

- [x] **Linked Lists**
    - [x] Description:
        - [x] https://www.coursera.org/learn/data-structures/lecture/kHhgK/singly-linked-lists
        - [x] Lynda.com:
            - https://www.lynda.com/Developer-Programming-Foundations-tutorials/Introduction-lists/149042/177115-4.html
            - https://www.lynda.com/Developer-Programming-Foundations-tutorials/Understanding-basic-list-implementations/149042/177116-4.html
            - https://www.lynda.com/Developer-Programming-Foundations-tutorials/Using-singly-doubly-linked-lists/149042/177117-4.html
            - https://www.lynda.com/Developer-Programming-Foundations-tutorials/List-support-across-languages/149042/177118-4.html
    - [x] C Code: https://www.youtube.com/watch?v=QN6FPiD0Gzo
            - not the whole video, just portions about Node struct and memory allocation.
    - [x] Linked List vs Arrays:
        - https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/rjBs9/core-linked-lists-vs-arrays
        - https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/QUaUd/in-the-real-world-lists-vs-arrays
    - [x] why you should avoid linked lists:
        - https://www.youtube.com/watch?v=YQs6IC-vgmo
    - [x] Gotcha: you need pointer to pointer knowledge:
        (for when you pass a pointer to a function that may change the address where that pointer points)
        This page is just to get a grasp on ptr to ptr. I don't recommend this list traversal style. Readability and maintainability suffer due to cleverness.
        - https://www.eskimo.com/~scs/cclass/int/sx8.html
    - [x] implement (I did with tail pointer & without):
        - [x] size() - returns number of data elements in list
        - [x] empty() - bool returns true if empty
        - [x] value_at(index) - returns the value of the nth item (starting at 0 for first)
        - [x] push_front(value) - adds an item to the front of the list
        - [x] pop_front() - remove front item and return its value
        - [x] push_back(value) - adds an item at the end
        - [x] pop_back() - removes end item and returns its value
        - [x] front() - get value of front item
        - [x] back() - get value of end item
        - [x] insert(index, value) - insert value at index, so current item at that index is pointed to by new item at index
        - [x] erase(index) - removes node at given index
        - [x] value_n_from_end(n) - returns the value of the node at nth position from the end of the list
        - [x] reverse() - reverses the list
        - [x] remove_value(value) - removes the first item in the list with this value
    - [x] Doubly-linked List
        - Description: https://www.coursera.org/learn/data-structures/lecture/jpGKD/doubly-linked-lists
        - No need to implement

- [x] **Stack**
    - [x] https://www.coursera.org/learn/data-structures/lecture/UdKzQ/stacks
    - [x] https://class.coursera.org/algs4partI-010/lecture/18
    - [x] https://class.coursera.org/algs4partI-010/lecture/19
    - [x] https://www.lynda.com/Developer-Programming-Foundations-tutorials/Using-stacks-last-first-out/149042/177120-4.html
    - [x] Will not implement. Implementing with array is trivial.

- [x] **Queue**
    - [x] https://www.lynda.com/Developer-Programming-Foundations-tutorials/Using-queues-first-first-out/149042/177122-4.html
    - [x] https://class.coursera.org/algs4partI-010/lecture/20
    - [x] https://www.coursera.org/learn/data-structures/lecture/EShpq/queue
    - [x] Circular buffer/FIFO: https://en.wikipedia.org/wiki/Circular_buffer
    - [x] https://class.coursera.org/algs4partI-010/lecture/23
    - [x] https://www.lynda.com/Developer-Programming-Foundations-tutorials/Priority-queues-deques/149042/177123-4.html
    - [x] Implement using linked-list, with tail pointer:
        - enqueue(value) - adds value at position at tail
        - dequeue() - returns value and removes least recently added element (front)
        - empty()
    - [x] Implement using fixed-sized array:
        - enqueue(value) - adds item at end of available storage
        - dequeue() - returns value and removes least recently added element
        - empty()
        - full()
    - [x] Cost:
        - a bad implementation using linked list where you enqueue at head and dequeue at tail would be O(n)
            because you'd need the next to last element, causing a full traversal each dequeue
        - enqueue: O(1) (amortized, linked list and array [probing])
        - dequeue: O(1) (linked list and array)
        - empty: O(1) (linked list and array)

- [x] **Hash table**
    - [x] https://www.lynda.com/Developer-Programming-Foundations-tutorials/Understanding-hash-functions/149042/177126-4.html
    - [x] https://www.lynda.com/Developer-Programming-Foundations-tutorials/Using-hash-tables/149042/177127-4.html
    - [x] https://www.lynda.com/Developer-Programming-Foundations-tutorials/Supporting-hashing/149042/177128-4.html
    - [x] https://www.lynda.com/Developer-Programming-Foundations-tutorials/Language-support-hash-tables/149042/177129-4.html
    - [x] https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/m7UuP/core-hash-tables
    - [x] https://www.youtube.com/watch?v=C4Kc8xzcA68
    - [x] https://class.coursera.org/algs4partI-010/lecture/52
    - [x] https://class.coursera.org/algs4partI-010/lecture/53
    - [x] https://class.coursera.org/algs4partI-010/lecture/55
    - [x] https://class.coursera.org/algs4partI-010/lecture/56
    - [x] https://www.coursera.org/learn/data-structures/home/week/3
    - [x] https://www.coursera.org/learn/data-structures/lecture/NYZZP/phone-book-problem
    - [x] distributed hash tables:
        - https://www.coursera.org/learn/data-structures/lecture/DvaIb/instant-uploads-and-storage-optimization-in-dropbox
        - https://www.coursera.org/learn/data-structures/lecture/tvH8H/distributed-hash-tables
    - [x] MIT:
        - https://www.youtube.com/watch?v=0M_kIqhwbFo&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=8
        - https://www.youtube.com/watch?v=BRO7mVIFt08&index=9&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb
        - https://www.youtube.com/watch?v=rvdJDijO2Ro&index=10&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb
    - [x] implement with array using linear probing
        - hash(k, m) - m is size of hash table
        - add(key, value) - if key already exists, update value
        - exists(key)
        - get(key)
        - remove(key)

## More Knowledge

- [x] **Binary search:**
    - [x] https://www.youtube.com/watch?v=D5SrAga1pno
    - [x] https://www.khanacademy.org/computing/computer-science/algorithms/binary-search/a/binary-search
    - [x] detail: https://www.topcoder.com/community/data-science/data-science-tutorials/binary-search/
    - [x] Implement:
        - binary search (on sorted array of integers)
        - binary search using recursion

- [x] **Bitwise operations**
    - [x] Get a really good understanding of manipulating bits with: &, |, ^, ~, >>, <<
        - [x] words: https://en.wikipedia.org/wiki/Word_(computer_architecture)
        - [x] Good intro:
            https://www.youtube.com/watch?v=7jkIUgLC29I
        - [x] https://www.youtube.com/watch?v=d0AwjSpNXR0
        - [x] https://en.wikipedia.org/wiki/Bit_manipulation
        - [x] https://en.wikipedia.org/wiki/Bitwise_operation
        - [x] https://graphics.stanford.edu/~seander/bithacks.html
        - [x] http://bits.stephan-brumme.com/
        - [x] http://bits.stephan-brumme.com/interactive.html
    - [x] 2s and 1s complement
        - https://www.youtube.com/watch?v=lKTsv6iVxV4
        - https://en.wikipedia.org/wiki/Ones%27_complement
        - https://en.wikipedia.org/wiki/Two%27s_complement
    - [x] count set bits
        - https://youtu.be/Hzuzo9NJrlc
        - https://graphics.stanford.edu/~seander/bithacks.html#CountBitsSetKernighan
        - http://stackoverflow.com/questions/109023/how-to-count-the-number-of-set-bits-in-a-32-bit-integer
    - [x] round to next power of 2:
        - http://bits.stephan-brumme.com/roundUpToNextPowerOfTwo.html
    - [x] swap values:
        - http://bits.stephan-brumme.com/swap.html
    - [x] absolute value:
        - http://bits.stephan-brumme.com/absInteger.html

- [x] **Parity & Hamming Code**
    - [x] Parity:
        - https://www.youtube.com/watch?v=DdMcAUlxh1M
    - [x] Hamming Code:
        - Error detection: https://www.youtube.com/watch?v=1A_NcXxdoCc
        - Error correction: https://www.youtube.com/watch?v=JAMLuxdHH8o
    - [x] Error Checking:
        - https://www.youtube.com/watch?v=wbH2VxzmoZk

## Trees

- [x] Notes:
    - [x] Series: https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/ovovP/core-trees
    - [x] Series: https://www.coursera.org/learn/data-structures/lecture/95qda/trees
    - basic tree construction
    - traversal
    - manipulation algorithms
    - BFS (breadth-first search)
        - MIT: https://www.youtube.com/watch?v=s-CYnVz-uh4&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=13
        - level order (BFS, using queue)
            time complexity: O(n)
            space complexity: best: O(1), worst: O(n/2)=O(n)
    - DFS (depth-first search)
        - MIT: https://www.youtube.com/watch?v=AfSk24UTFS8&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=14
        - notes:
            time complexity: O(n)
            space complexity:
                best: O(log n) - avg. height of tree
                worst: O(n)
        - inorder (DFS: left, self, right)
        - postorder (DFS: left, right, self)
        - preorder (DFS: self, left, right)

- [x] **Binary search trees: BSTs**
    - [x] Series: https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/p82sw/core-introduction-to-binary-search-trees
    - [x] Series: https://class.coursera.org/algs4partI-010/lecture/43
        - starts with symbol table and goes through BST applications
    - [x] https://www.coursera.org/learn/data-structures/lecture/E7cXP/introduction
    - [x] MIT: https://www.youtube.com/watch?v=9Jry5-82I68
    - C/C++:
        - [x] https://www.youtube.com/watch?v=COZK7NATh4k&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=28
        - [x] https://www.youtube.com/watch?v=hWokyBoo0aI&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=29
        - [x] https://www.youtube.com/watch?v=Ut90klNN264&index=30&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P
        - [x] https://www.youtube.com/watch?v=_pnqMz5nrRs&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=31
        - [x] https://www.youtube.com/watch?v=9RHO6jU--GU&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=32
        - [x] https://www.youtube.com/watch?v=86g8jAQug04&index=33&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P
        - [x] https://www.youtube.com/watch?v=gm8DUJJhmY4&index=34&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P
        - [x] https://www.youtube.com/watch?v=yEwSGhSsT0U&index=35&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P
        - [x] https://www.youtube.com/watch?v=gcULXE7ViZw&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=36
        - [x] https://www.youtube.com/watch?v=5cPbNCrdotA&index=37&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P

- [x] **Balanced binary trees**
    - Know least one type of balanced binary tree (and know how it's implemented):

    - [x] **AVL trees**
        -[x] MIT: https://www.youtube.com/watch?v=FNeL18KsWPc&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=6
        -[x] https://www.coursera.org/learn/data-structures/lecture/Qq5E0/avl-trees
        -[x] https://www.coursera.org/learn/data-structures/lecture/PKEBC/avl-tree-implementation
        -[x] https://www.coursera.org/learn/data-structures/lecture/22BgE/split-and-merge

    - [ ] **red/black trees**
        - https://class.coursera.org/algs4partI-010/lecture/50

    - [ ] **splay trees**
        - https://www.coursera.org/learn/data-structures/lecture/O9nZ6/splay-trees
        - UCB: https://www.youtube.com/watch?v=G5QIXywcJlY
        - https://www.youtube.com/watch?v=QnPl_Y6EqMo

    - [ ] **B-Trees**
        - fun fact: B could stand for Boeing, Balanced, or Bayer (co-inventor)
        - https://en.wikipedia.org/wiki/B-tree
        - https://class.coursera.org/algs4partI-010/lecture/51

    - [ ] **2-3 search trees**
        - 2-3 and B-trees: https://class.coursera.org/algs4partI-010/lecture/49
        - https://www.youtube.com/watch?v=TOb1tuEZ2X4&index=5&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp

- [ ] **N-ary trees**
    - https://en.wikipedia.org/wiki/K-ary_tree

- [ ] **Tries**
    - https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/08Xyf/core-introduction-to-tries
    - https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/PvlZW/core-performance-of-tries
    - https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/DFvd3/core-implementing-a-trie

- [ ] **Heap (data structure):**
    - https://en.wikipedia.org/wiki/Heap_(data_structure)
    - https://www.coursera.org/learn/data-structures/lecture/2OpTs/introduction
    - https://www.coursera.org/learn/data-structures/lecture/z3l9N/naive-implementations
    - https://www.coursera.org/learn/data-structures/lecture/GRV2q/binary-trees
    - https://www.coursera.org/learn/data-structures/supplement/S5xxz/tree-height-remark
    - https://www.coursera.org/learn/data-structures/lecture/0g1dl/basic-operations
    - https://www.coursera.org/learn/data-structures/lecture/gl5Ni/complete-binary-trees
    - https://www.coursera.org/learn/data-structures/lecture/HxQo9/pseudocode
    - see: https://class.coursera.org/algs4partI-010/lecture
    - https://class.coursera.org/algs4partI-010/lecture/39

- [ ] **Binary Heap:**
    Min Heap / Max Heap

- [ ] **Disjoint Sets:**
    - https://www.coursera.org/learn/data-structures/lecture/JssSY/overview
    - https://www.coursera.org/learn/data-structures/lecture/EM5D0/naive-implementations
    - https://www.coursera.org/learn/data-structures/lecture/Mxu0w/trees
    - https://www.coursera.org/learn/data-structures/lecture/qb4c2/union-by-rank
    - https://www.coursera.org/learn/data-structures/lecture/Q9CVI/path-compression
    - https://www.coursera.org/learn/data-structures/lecture/GQQLN/analysis-optional

- [ ] **Priority Queue**
    - Notes:
        - visualized as a tree, but is usually linear in storage (array, linked list)
    - https://en.wikipedia.org/wiki/Priority_queue


## Graphs

- Notes:
    - There are three basic ways to represent a graph in memory:
        - objects and pointers
        - matrix
        - adjacency list
    - Familiarize yourself with each representation and its pros & cons
    - BFS and DFS - know their computational complexity, their tradeoffs, and how to implement them in real code
    - If you get a chance, try to study up on fancier algorithms:
        - Dijkstra's algorithm
            - https://en.wikipedia.org/wiki/Dijkstra%27s_algorithm
        - A*
            - https://en.wikipedia.org/wiki/A*_search_algorithm
    - When asked a question, look for a graph-based solution first, then move on if none.

- Compute Strongly Connected Components
    - [ ] https://www.coursera.org/learn/algorithms-on-graphs/home/week/5

- Implement:

    - [ ] Dijkstra's algorithm
    - [ ] A*

You'll get more graph practice in Skiena's book (see Books section below) and the interview books

## Sorting

- [ ] Notes:
    - [ ] Implement & know best case/worst case, average complexity of each:
        - no bubble sort - it's terrible - O(n^2)
    - [ ] stability in sorting algorithms:
        - http://stackoverflow.com/questions/1517793/stability-in-sorting-algorithms
        - http://www.geeksforgeeks.org/stability-in-sorting-algorithms/
    - [ ] Which algorithms can be used on linked lists?
    - [ ] Which on arrays? Which on both?
    - [ ] Is Quicksort stable?

- [ ] Implement:
    - [ ] Mergesort
    - [ ] Quicksort
    - [ ] Insertion Sort
    - [ ] Selection Sort

- For Curiosity:
     - [ ] Radix Sort: https://www.youtube.com/watch?v=xhr26ia4k38

## Even More Knowledge

- [ ] Caches
    - LRU cache

- [ ] NP and NP Complete
    - Know about the most famous classes of NP-complete problems, such as traveling salesman and the knapsack problem,
        and be able to recognize them when an interviewer asks you them in disguise.
    - Know what NP-complete means.

- [ ] Recursion
    -  when it is appropriate to use it

- [ ] open-ended problems
    - manipulate strings
    - manipulate patterns

- [ ] Combinatorics (n choose k)

- [ ] Probability
    - https://www.youtube.com/watch?v=sZkAAk9Wwa4
    - https://www.youtube.com/watch?v=dNaJg-mLobQ

- [ ] Dynamic Programming

- [ ] Scheduling

- [ ] Weighted random sampling

- [ ] Implement system routines

- [ ] Design patterns:
    - description:
        - https://www.lynda.com/Developer-Programming-Foundations-tutorials/Foundations-Programming-Design-Patterns/135365-2.html
        - Patterns: https://www.youtube.com/playlist?list=PLF206E906175C7E07
        - UML: https://www.youtube.com/playlist?list=PLGLfVvz_LVvQ5G-LdJ8RLqe-ndo7QITYc
    - [ ] strategy
    - [ ] singleton
    - [ ] adapter
    - [ ] prototype
    - [ ] decorator
    - [ ] visitor
    - [ ] factory

- [ ] **Operating Systems (25 videos):**
    - https://www.youtube.com/watch?v=-KWd_eQYLwY&index=2&list=PL-XXv-cvA_iBDyz-ba4yDskqMDY6A1w_c
    - https://www.quora.com/What-is-the-difference-between-a-process-and-a-thread
    Covers:
        - Processes, Threads, Concurrency issues
            - difference between processes and threads
            - processes
            - threads
            - locks
            - mutexes
            - semaphores
            - monitors
            - how they work
            - deadlock
            - livelock
        - CPU activity, interrupts, context switching
        - Modern concurrency constructs with multicore processors
        - Process resource needs (memory: code, static storage, stack, heap, and also file descriptors, i/o)
        - Thread resource needs (shares above with other threads in 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++:
        https://www.youtube.com/playlist?list=PL5jc9xFGsL8E12so1wlMS0r0hTQoJL74M
        - stopped here: https://www.youtube.com/watch?v=_N0B5ua7oN8&list=PL5jc9xFGsL8E12so1wlMS0r0hTQoJL74M&index=4

- [ ] **Data handling:**
    - see scalability options below
    - Distill large data sets to single values
    - Transform one data set to another
    - Handling obscenely large amounts of data

- [ ] **System design**
    - https://www.quora.com/How-do-I-prepare-to-answer-design-questions-in-a-technical-interview?redirected_qid=1500023
    - features sets
    - interfaces
    - class hierarchies
    - designing a system under certain constraints
    - simplicity and robustness
    - tradeoffs
    - performance analysis and optimization

- [ ] **Familiarize yourself with a unix-based code editor: emacs & vi(m)**
    - suggested by Yegge
    - vi(m):
        - https://www.youtube.com/watch?v=5givLEMcINQ&index=1&list=PL13bz4SHGmRxlZVmWQ9DvXo1fEg4UdGkr
        - set of 4:
            - https://www.youtube.com/watch?v=SI8TeVMX8pk
            - https://www.youtube.com/watch?v=F3OO7ZIOaJE
            - https://www.youtube.com/watch?v=ZYEccA_nMaI
            - https://www.youtube.com/watch?v=1lYD5gwgZIA
    - emacs:
        - https://www.youtube.com/watch?v=hbmV1bnQ-i0
        - set of 3:
            - https://www.youtube.com/watch?v=ujODL7MD04Q
            - https://www.youtube.com/watch?v=XWpsRupJ4II
            - https://www.youtube.com/watch?v=paSgzPso-yc
        - https://www.youtube.com/watch?v=JWD1Fpdd4Pc

- [ ] **Be able to use unix command line tools:**
    - suggested by Yegge
    - bash
    - grep
    - sed
    - awk
    - curl or wget

- [ ] **Testing**
    - how unit testing works
    - what are mock onbjects
    - what is integration testing
    - what is dependency injection

## Books

#### Mentioned in Google Coaching:

- [ ] The Algorithm Design Manual (Skiena)
    - Book (can rent on kindle):
        - http://www.amazon.com/Algorithm-Design-Manual-Steven-Skiena/dp/1849967202
    - Answers:
        - http://www.algorithm.cs.sunysb.edu/algowiki/index.php/The_Algorithms_Design_Manual_(Second_Edition)

- [ ] Algorithms and Programming: Problems and Solutions:
    http://www.amazon.com/Algorithms-Programming-Solutions-Alexander-Shen/dp/0817638474


    Once you've understood everything in the daily plan, read and do exercises from
    the books below. Then move to coding challenges (further down below)


**Read first:**
- [ ] Programming Interviews Exposed: Secrets to Landing Your Next Job, 2nd Edition:
    http://www.wiley.com/WileyCDA/WileyTitle/productCd-047012167X.html

**Read second:**
- [ ] Cracking the Coding Interview, 6th Edition:
    - http://www.amazon.com/Cracking-Coding-Interview-6th-Programming/dp/0984782850/

#### Additional books (not suggested by Google but I added):

- [x] C Programming Language, Vol 2

- [x] C++ Primer Plus, 6th Edition

- [ ] Introduction to Algorithms
    - https://www.amazon.com/Introduction-Algorithms-3rd-MIT-Press/dp/0262033844

- [ ] Programming Pearls:
    - http://www.amazon.com/Programming-Pearls-2nd-Jon-Bentley/dp/0201657880

If you see people reference "The Google Resume", it was a book replaced by "Cracking the Coding Interview".

## About Google

- [ ] How Search Works:
    - [ ] https://www.google.com/insidesearch/howsearchworks/thestory/
    - [ ] https://www.youtube.com/watch?v=BNHR6IQJGZs
    - [ ] https://www.google.com/insidesearch/howsearchworks/

## 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

## Papers:

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
    - http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/43835.pdf

Borg, Omega, and Kubernetes
    - http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/44843.pdf

Continuous Pipelines at Google
    - http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/43790.pdf

AddressSanitizer: A Fast Address Sanity Checker
    - http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/37752.pdf

## 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.

- https://courses.csail.mit.edu/iap/interview/materials.php

The Best:
- LeetCode: https://leetcode.com/
- Project Euler: https://projecteuler.net/index.php?section=problems
- TopCoder: https://www.topcoder.com/

More:
- HackerRank: https://www.hackerrank.com/
- Codility: https://codility.com/programmers/
- InterviewCake: https://www.interviewcake.com/
- InterviewBit: https://www.interviewbit.com/invite/icjf


## Once you're closer to the interview:

- [ ] Cracking The Coding Interview Set 2:
    - https://www.youtube.com/watch?v=4NIb9l3imAo
    - https://www.youtube.com/watch?v=Eg5-tdAwclo
    - https://www.youtube.com/watch?v=1fqxMuPmGak

## Your Resume

- http://steve-yegge.blogspot.co.uk/2007_09_01_archive.html


## Be thinking of for when the interview comes:

- Think of about 20 interview questions you'll get, along 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 Google 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 is 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?

---

## Additional Resources

    Everything below is my recommendation, not Google's, and you may not have enough time to
    learn, watch or read them all. That's ok. I may not either.

- [ ] Vector calculus

- [ ] Computer Security:
    - MIT (23 videos): https://www.youtube.com/playlist?list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh

- [ ] Information theory:
    - Markov processes:
        - https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/waxgx/core-markov-text-generation
        - https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/gZhiC/core-implementing-markov-text-generation
    - https://www.khanacademy.org/computing/computer-science/informationtheory/moderninfotheory/v/symbol-rate-information-theory
    - includes Markov chain

- [ ] Bloom Filter
    - https://www.youtube.com/watch?v=-SuTGoFYjZs
    - http://blog.michaelschmatz.com/2016/04/11/how-to-write-a-bloom-filter-cpp/

- [ ] Fast Fourier Transform
    - http://jakevdp.github.io/blog/2013/08/28/understanding-the-fft/

- [ ] Machine Learning:
    - great course: https://www.coursera.org/learn/machine-learning
    - http://www.analyticsvidhya.com/blog/2016/04/neural-networks-python-theano/
    - http://www.dataschool.io/

- [ ] Parallel Programming:
    - https://www.coursera.org/learn/parprog1/home/week/1

- [ ] String search algorithms:
    Knuth-Morris-Pratt (KMP):
        - https://en.wikipedia.org/wiki/Knuth%E2%80%93Morris%E2%80%93Pratt_algorithm
        - https://www.youtube.com/watch?v=2ogqPWJSftE
    Boyer–Moore string search algorithm
        - https://en.wikipedia.org/wiki/Boyer%E2%80%93Moore_string_search_algorithm
        - https://www.youtube.com/watch?v=xYBM0_dChRE

## Videos

Sit back and enjoy. "netflix and skill" :P

- [ ] Scalability:
    - https://www.youtube.com/watch?v=9nWyWwY2Onc
    - https://www.youtube.com/watch?v=H4vMcD7zKM0

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

- [ ] MIT 6.042: Math for CS (25 videos):
    - https://www.youtube.com/watch?v=L3LMbpZIKhQ&list=PLB7540DEDD482705B

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

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

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

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

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

- [ ] Stanford: Programming Paradigms (17 videos)
    - Course on C and C++
    - https://www.youtube.com/watch?v=jTSvthW34GU&list=PLC0B8B318B7394B6F&nohtml5=False

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

- [ ] Introduction to Cryptography:
    - https://www.youtube.com/watch?v=2aHkqB2-46k&feature=youtu.be

## Maybe

http://www.gainlo.co/ - Mock interviewers from big companies

## Code References

For review questions in C book:
    https://github.com/lekkas/c-algorithms

## Once You've Got The Job

This is mainly for me.

- [ ] Books:
    - [ ] Clean Code
    - [ ] Code Complete
    - [ ] How to Prove It: A Structured Approach, 2nd Edition
    - [ ] Unix Power Tools, Third Edition

- [x] C++ Seasoning:
    - https://www.youtube.com/watch?v=qH6sSOr-yk8

- [x] Better Code: Data Structures:
    - https://www.youtube.com/watch?v=sWgDk-o-6ZE

- [ ] C++ Talks at CPPCon:
    - https://www.youtube.com/watch?v=hEx5DNLWGgA&index=2&list=PLHTh1InhhwT75gykhs7pqcR_uSiG601oh

- [ ] MIT CMS.611J Creating Video Games, Fall 2014
    - https://www.youtube.com/watch?v=pfDfriSjFbY&list=PLUl4u3cNGP61V4W6yRm1Am5zI94m33dXk

- [ ] Compilers:
    - https://class.coursera.org/compilers-004/lecture

- [ ] Computer and processor architecture:
    - https://class.coursera.org/comparch-003/lecture

- [ ] Long series of C++ videos:
    - https://www.youtube.com/playlist?list=PLfVsf4Bjg79Cu5MYkyJ-u4SyQmMhFeC1C

## Done

You're never really done. Keep learning.