Updating the list of what you need to know (for entry-level engineers) based on recent info.
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John Washam
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README.md
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README.md
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@ -13,6 +13,9 @@ There are extra items I added at the bottom that may come up in the interview or
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Steve Yegge's "[Get that job at Google](http://steve-yegge.blogspot.com/2008/03/get-that-job-at-google.html)" and are reflected
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sometimes word-for-word in Google's coaching notes.
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I've pared down what you need to know from what Yegge says for new software engineers. If you have many years of experience, expect a harder interview.
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[Read more here](https://googleyasheck.com/what-you-need-to-know-for-your-google-interview-and-what-you-dont/).
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---
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## Table of Contents
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@ -46,11 +49,20 @@ sometimes word-for-word in Google's coaching notes.
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- [Trees - Notes & Background](#trees---notes--background)
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- [Binary search trees: BSTs](#binary-search-trees-bsts)
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- [Heap / Priority Queue / Binary Heap](#heap--priority-queue--binary-heap)
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- [Tries](#tries)
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- [Balanced search trees](#balanced-search-trees)
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- [N-ary (K-ary, M-ary) trees](#n-ary-k-ary-m-ary-trees)
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- balanced search trees (general concept, not details)
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- traversals: preorder, inorder, postorder, BFS, DFS
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- [Sorting](#sorting)
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- selection
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- insertion
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- heapsort
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- quicksort
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- merge sort
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- [Graphs](#graphs)
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- directed
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- undirected
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- adjacency matrix
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- adjacency list
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- traversals: BFS, DFS
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- [Even More Knowledge](#even-more-knowledge)
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- [Recursion](#recursion)
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- [Dynamic Programming](#dynamic-programming)
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@ -58,12 +70,12 @@ sometimes word-for-word in Google's coaching notes.
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- [NP, NP-Complete and Approximation Algorithms](#np-np-complete-and-approximation-algorithms)
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- [Caches](#caches)
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- [Processes and Threads](#processes-and-threads)
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- [System Design, Scalability, Data Handling](#system-design-scalability-data-handling)
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- [Papers](#papers)
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- [Testing](#testing)
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- [Scheduling](#scheduling)
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- [Implement system routines](#implement-system-routines)
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- [String searching & manipulations](#string-searching--manipulations)
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- [System Design, Scalability, Data Handling](#system-design-scalability-data-handling) (if you have 4+ years experience)
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- [Final Review](#final-review)
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- [Coding Question Practice](#coding-question-practice)
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- [Coding exercises/challenges](#coding-exerciseschallenges)
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@ -88,7 +100,7 @@ sometimes word-for-word in Google's coaching notes.
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- [Entropy](#entropy)
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- [Cryptography](#cryptography)
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- [Compression](#compression)
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- [Networking](#networking)
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- [Networking](#networking) (if you have networking experience, expect questions)
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- [Computer Security](#computer-security)
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- [Garbage collection](#garbage-collection)
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- [Parallel Programming](#parallel-programming)
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@ -100,6 +112,16 @@ sometimes word-for-word in Google's coaching notes.
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- [Locality-Sensitive Hashing](#locality-sensitive-hashing)
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- [van Emde Boas Trees](#van-emde-boas-trees)
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- [Augmented Data Structures](#augmented-data-structures)
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- [Tries](#tries)
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- [N-ary (K-ary, M-ary) trees](#n-ary-k-ary-m-ary-trees)
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- [Balanced search trees](#balanced-search-trees)
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- AVL trees
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- Splay trees
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- Red/black trees
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- 2-3 search trees
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- 2-3-4 Trees (aka 2-4 trees)
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- N-ary (K-ary, M-ary) trees
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- B-Trees
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- [k-D Trees](#k-d-trees)
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- [Skip lists](#skip-lists)
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- [Network Flows](#network-flows)
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@ -645,113 +667,6 @@ Write code on a whiteboard or paper, not a computer. Test with some sample input
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- [ ] heap_sort() - take an unsorted array and turn it into a sorted array in-place using a max heap
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- note: using a min heap instead would save operations, but double the space needed (cannot do in-place).
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- ### Tries
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- Note there are different kinds of tries. Some have prefixes, some don't, and some use string instead of bits
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to track the path.
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- I read through code, but will not implement.
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- [ ] [Sedgewick - Tries (3 videos)](https://www.youtube.com/playlist?list=PLe-ggMe31CTe9IyG9MB8vt5xUJeYgOYRQ)
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- [ ] [1. R Way Tries](https://www.youtube.com/watch?v=buq2bn8x3Vo&index=3&list=PLe-ggMe31CTe9IyG9MB8vt5xUJeYgOYRQ)
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- [ ] [2. Ternary Search Tries](https://www.youtube.com/watch?v=LelV-kkYMIg&index=2&list=PLe-ggMe31CTe9IyG9MB8vt5xUJeYgOYRQ)
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- [ ] [3. Character Based Operations](https://www.youtube.com/watch?v=00YaFPcC65g&list=PLe-ggMe31CTe9IyG9MB8vt5xUJeYgOYRQ&index=1)
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- [ ] [Notes on Data Structures and Programming Techniques](http://www.cs.yale.edu/homes/aspnes/classes/223/notes.html#Tries)
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- [ ] Short course videos:
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- [ ] [Introduction To Tries (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/08Xyf/core-introduction-to-tries)
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- [ ] [Performance Of Tries (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/PvlZW/core-performance-of-tries)
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- [ ] [Implementing A Trie (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/DFvd3/core-implementing-a-trie)
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- [ ] [The Trie: A Neglected Data Structure](https://www.toptal.com/java/the-trie-a-neglected-data-structure)
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- [ ] [TopCoder - Using Tries](https://www.topcoder.com/community/data-science/data-science-tutorials/using-tries/)
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- [ ] [Stanford Lecture (real world use case) (video)](https://www.youtube.com/watch?v=TJ8SkcUSdbU)
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- [ ] [MIT, Advanced Data Structures, Strings (can get pretty obscure about halfway through)](https://www.youtube.com/watch?v=NinWEPPrkDQ&index=16&list=PLUl4u3cNGP61hsJNdULdudlRL493b-XZf)
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- ### Balanced search trees
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- Know least one type of balanced binary tree (and know how it's implemented):
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- "Among balanced search trees, AVL and 2/3 trees are now passé, and red-black trees seem to be more popular.
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A particularly interesting self-organizing data structure is the splay tree, which uses rotations
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to move any accessed key to the root." - Skiena
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- Of these, I chose to implement a splay tree. From what I've read, you won't implement a
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balanced search tree in your interview. But I wanted exposure to coding one up
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and let's face it, splay trees are the bee's knees. I did read a lot of red-black tree code.
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- splay tree: insert, search, delete functions
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If you end up implementing red/black tree try just these:
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- search and insertion functions, skipping delete
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- I want to learn more about B-Tree since it's used so widely with very large data sets.
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- [ ] [Self-balancing binary search tree](https://en.wikipedia.org/wiki/Self-balancing_binary_search_tree)
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- [ ] **AVL trees**
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- In practice:
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From what I can tell, these aren't used much in practice, but I could see where they would be:
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The AVL tree is another structure supporting O(log n) search, insertion, and removal. It is more rigidly
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balanced than red–black trees, leading to slower insertion and removal but faster retrieval. This makes it
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attractive for data structures that may be built once and loaded without reconstruction, such as language
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dictionaries (or program dictionaries, such as the opcodes of an assembler or interpreter).
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- [ ] [MIT AVL Trees / AVL Sort (video)](https://www.youtube.com/watch?v=FNeL18KsWPc&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=6)
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- [ ] [AVL Trees (video)](https://www.coursera.org/learn/data-structures/lecture/Qq5E0/avl-trees)
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- [ ] [AVL Tree Implementation (video)](https://www.coursera.org/learn/data-structures/lecture/PKEBC/avl-tree-implementation)
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- [ ] [Split And Merge](https://www.coursera.org/learn/data-structures/lecture/22BgE/split-and-merge)
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- [ ] **Splay trees**
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- In practice:
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Splay trees are typically used in the implementation of caches, memory allocators, routers, garbage collectors,
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data compression, ropes (replacement of string used for long text strings), in Windows NT (in the virtual memory,
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networking, and file system code) etc.
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- [ ] [CS 61B: Splay Trees (video)](https://www.youtube.com/watch?v=Najzh1rYQTo&index=23&list=PL-XXv-cvA_iAlnI-BQr9hjqADPBtujFJd)
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- [ ] MIT Lecture: Splay Trees:
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- Gets very mathy, but watch the last 10 minutes for sure.
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- [Video](https://www.youtube.com/watch?v=QnPl_Y6EqMo)
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- [ ] **2-3 search trees**
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- In practice:
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2-3 trees have faster inserts at the expense of slower searches (since height is more compared to AVL trees).
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- You would use 2-3 tree very rarely because its implementation involves different types of nodes. Instead, people use Red Black trees.
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- [ ] [23-Tree Intuition and Definition (video)](https://www.youtube.com/watch?v=C3SsdUqasD4&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6&index=2)
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- [ ] [Binary View of 23-Tree](https://www.youtube.com/watch?v=iYvBtGKsqSg&index=3&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6)
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- [ ] [2-3 Trees (student recitation) (video)](https://www.youtube.com/watch?v=TOb1tuEZ2X4&index=5&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp)
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- [ ] **2-3-4 Trees (aka 2-4 trees)**
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- In practice:
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For every 2-4 tree, there are corresponding red–black trees with data elements in the same order. The insertion and deletion
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operations on 2-4 trees are also equivalent to color-flipping and rotations in red–black trees. This makes 2-4 trees an
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important tool for understanding the logic behind red–black trees, and this is why many introductory algorithm texts introduce
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2-4 trees just before red–black trees, even though **2-4 trees are not often used in practice**.
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- [ ] [CS 61B Lecture 26: Balanced Search Trees (video)](https://www.youtube.com/watch?v=zqrqYXkth6Q&index=26&list=PL4BBB74C7D2A1049C)
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- [ ] [Bottom Up 234-Trees (video)](https://www.youtube.com/watch?v=DQdMYevEyE4&index=4&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6)
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- [ ] [Top Down 234-Trees (video)](https://www.youtube.com/watch?v=2679VQ26Fp4&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6&index=5)
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- [ ] **B-Trees**
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- fun fact: it's a mystery, but the B could stand for Boeing, Balanced, or Bayer (co-inventor)
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- In Practice:
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B-Trees are widely used in databases. Most modern filesystems use B-trees (or Variants). In addition to
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its use in databases, the B-tree is also used in filesystems to allow quick random access to an arbitrary
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block in a particular file. The basic problem is turning the file block i address into a disk block
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(or perhaps to a cylinder-head-sector) address.
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- [ ] [B-Tree](https://en.wikipedia.org/wiki/B-tree)
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- [ ] [Introduction to B-Trees (video)](https://www.youtube.com/watch?v=I22wEC1tTGo&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6&index=6)
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- [ ] [B-Tree Definition and Insertion (video)](https://www.youtube.com/watch?v=s3bCdZGrgpA&index=7&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6)
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- [ ] [B-Tree Deletion (video)](https://www.youtube.com/watch?v=svfnVhJOfMc&index=8&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6)
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- [ ] [MIT 6.851 - Memory Hierarchy Models (video)](https://www.youtube.com/watch?v=V3omVLzI0WE&index=7&list=PLUl4u3cNGP61hsJNdULdudlRL493b-XZf)
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- covers cache-oblivious B-Trees, very interesting data structures
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- the first 37 minutes are very technical, may be skipped (B is block size, cache line size)
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- [ ] **Red/black trees**
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- In practice:
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Red–black trees offer worst-case guarantees for insertion time, deletion time, and search time.
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Not only does this make them valuable in time-sensitive applications such as real-time applications,
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but it makes them valuable building blocks in other data structures which provide worst-case guarantees;
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for example, many data structures used in computational geometry can be based on red–black trees, and
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the Completely Fair Scheduler used in current Linux kernels uses red–black trees. In the version 8 of Java,
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the Collection HashMap has been modified such that instead of using a LinkedList to store identical elements with poor
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hashcodes, a Red-Black tree is used.
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- [ ] [Aduni - Algorithms - Lecture 4 (link jumps to starting point) (video)](https://youtu.be/1W3x0f_RmUo?list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&t=3871)
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- [ ] [Aduni - Algorithms - Lecture 5 (video)](https://www.youtube.com/watch?v=hm2GHwyKF1o&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=5)
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- [ ] [Black Tree](https://en.wikipedia.org/wiki/Red%E2%80%93black_tree)
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- [ ] [An Introduction To Binary Search And Red Black Tree](https://www.topcoder.com/community/data-science/data-science-tutorials/an-introduction-to-binary-search-and-red-black-trees/)
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- ### N-ary (K-ary, M-ary) trees
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- note: the N or K is the branching factor (max branches)
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- binary trees are a 2-ary tree, with branching factor = 2
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- 2-3 trees are 3-ary
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- [ ] [K-Ary Tree](https://en.wikipedia.org/wiki/K-ary_tree)
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## Sorting
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- [ ] Notes:
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@ -1002,9 +917,78 @@ You'll get more graph practice in Skiena's book (see Books section below) and th
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- [ ] [Keynote David Beazley - Topics of Interest (Python Asyncio)](https://www.youtube.com/watch?v=ZzfHjytDceU)
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- [ ] [Mutex in Python](https://www.youtube.com/watch?v=0zaPs8OtyKY)
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- ### Papers
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- These are Google papers and well-known papers.
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- Reading all from end to end with full comprehension will likely take more time than you have. I recommend being selective on papers and their sections.
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- [ ] [1978: Communicating Sequential Processes](http://spinroot.com/courses/summer/Papers/hoare_1978.pdf)
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- [implemented in Go](https://godoc.org/github.com/thomas11/csp)
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- [Love classic papers?](https://www.cs.cmu.edu/~crary/819-f09/)
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- [ ] [2003: The Google File System](http://static.googleusercontent.com/media/research.google.com/en//archive/gfs-sosp2003.pdf)
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- replaced by Colossus in 2012
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- [ ] [2004: MapReduce: Simplified Data Processing on Large Clusters]( http://static.googleusercontent.com/media/research.google.com/en//archive/mapreduce-osdi04.pdf)
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- mostly replaced by Cloud Dataflow?
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- [ ] [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)
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- [ ] [2012: Google's Colossus](https://www.wired.com/2012/07/google-colossus/)
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- paper not available
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- [ ] 2012: AddressSanitizer: A Fast Address Sanity Checker:
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- [paper](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/37752.pdf)
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- [video](https://www.usenix.org/conference/atc12/technical-sessions/presentation/serebryany)
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- [ ] 2013: Spanner: Google’s Globally-Distributed Database:
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- [paper](http://static.googleusercontent.com/media/research.google.com/en//archive/spanner-osdi2012.pdf)
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- [video](https://www.usenix.org/node/170855)
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- [ ] [2014: Machine Learning: The High-Interest Credit Card of Technical Debt](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/43146.pdf)
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- [ ] [2015: Continuous Pipelines at Google](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/43790.pdf)
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- [ ] [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)
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- [ ] [2015: TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems](http://download.tensorflow.org/paper/whitepaper2015.pdf )
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- [ ] [2015: How Developers Search for Code: A Case Study](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/43835.pdf)
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- [ ] [2016: Borg, Omega, and Kubernetes](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/44843.pdf)
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- ### Testing
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- To cover:
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- how unit testing works
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- what are mock objects
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- what is integration testing
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- what is dependency injection
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- [ ] [Agile Software Testing with James Bach (video)](https://www.youtube.com/watch?v=SAhJf36_u5U)
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- [ ] [Open Lecture by James Bach on Software Testing (video)](https://www.youtube.com/watch?v=ILkT_HV9DVU)
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- [ ] [Steve Freeman - Test-Driven Development (that’s not what we meant) (video)](https://vimeo.com/83960706)
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- [slides](http://gotocon.com/dl/goto-berlin-2013/slides/SteveFreeman_TestDrivenDevelopmentThatsNotWhatWeMeant.pdf)
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- [ ] [TDD is dead. Long live testing.](http://david.heinemeierhansson.com/2014/tdd-is-dead-long-live-testing.html)
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- [ ] [Is TDD dead? (video)](https://www.youtube.com/watch?v=z9quxZsLcfo)
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- [ ] [Video series (152 videos) - not all are needed (video)](https://www.youtube.com/watch?v=nzJapzxH_rE&list=PLAwxTw4SYaPkWVHeC_8aSIbSxE_NXI76g)
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- [ ] [Test-Driven Web Development with Python](http://www.obeythetestinggoat.com/pages/book.html#toc)
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- [ ] Dependency injection:
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- [ ] [video](https://www.youtube.com/watch?v=IKD2-MAkXyQ)
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- [ ] [Tao Of Testing](http://jasonpolites.github.io/tao-of-testing/ch3-1.1.html)
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- [ ] [How to write tests](http://jasonpolites.github.io/tao-of-testing/ch4-1.1.html)
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- ### Scheduling
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- in an OS, how it works
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- can be gleaned from Operating System videos
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- ### Implement system routines
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- understand what lies beneath the programming APIs you use
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- can you implement them?
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- ### String searching & manipulations
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- [ ] [Sedgewick - Suffix Arrays (video)](https://www.youtube.com/watch?v=HKPrVm5FWvg)
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- [ ] [Sedgewick - Substring Search (videos)](https://www.youtube.com/watch?v=2LvvVFCEIv8&list=PLe-ggMe31CTdAdjXB3lIuf2maubzo9t66&index=5)
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- [ ] [1. Introduction to Substring Search](https://www.youtube.com/watch?v=2LvvVFCEIv8&list=PLe-ggMe31CTdAdjXB3lIuf2maubzo9t66&index=5)
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- [ ] [2. Brute-Force Substring Search](https://www.youtube.com/watch?v=CcDXwIGEXYU&list=PLe-ggMe31CTdAdjXB3lIuf2maubzo9t66&index=4)
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- [ ] [3. Knuth-Morris Pratt](https://www.youtube.com/watch?v=n-7n-FDEWzc&index=3&list=PLe-ggMe31CTdAdjXB3lIuf2maubzo9t66)
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- [ ] [4. Boyer-Moore](https://www.youtube.com/watch?v=fI7Ch6pZXfM&list=PLe-ggMe31CTdAdjXB3lIuf2maubzo9t66&index=2)
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- [ ] [5. Rabin-Karp](https://www.youtube.com/watch?v=QzI0p6zDjK4&index=1&list=PLe-ggMe31CTdAdjXB3lIuf2maubzo9t66)
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- [ ] [Search pattern in text (video)](https://www.coursera.org/learn/data-structures/lecture/tAfHI/search-pattern-in-text)
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||||
If you need more detail on this subject, see "String Matching" section in [Additional Detail on Some Subjects](#additional-detail-on-some-subjects)
|
||||
|
||||
---
|
||||
|
||||
Scalability and System Design are very large topics with many topics and resources, since there is a lot to consider
|
||||
when designing a software/hardware system that can scale. Expect to spend quite a bit of time on this.
|
||||
|
||||
You can expect system design questions if you have 4+ years of experience
|
||||
|
||||
|
||||
- ### System Design, Scalability, Data Handling
|
||||
- Considerations from Yegge:
|
||||
|
|
@ -1147,71 +1131,6 @@ You'll get more graph practice in Skiena's book (see Books section below) and th
|
|||
- [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/)
|
||||
|
||||
- ### Papers
|
||||
- These are Google papers and well-known papers.
|
||||
- Reading all from end to end with full comprehension will likely take more time than you have. I recommend being selective on papers and their sections.
|
||||
- [ ] [1978: Communicating Sequential Processes](http://spinroot.com/courses/summer/Papers/hoare_1978.pdf)
|
||||
- [implemented in Go](https://godoc.org/github.com/thomas11/csp)
|
||||
- [Love classic papers?](https://www.cs.cmu.edu/~crary/819-f09/)
|
||||
- [ ] [2003: The Google File System](http://static.googleusercontent.com/media/research.google.com/en//archive/gfs-sosp2003.pdf)
|
||||
- replaced by Colossus in 2012
|
||||
- [ ] [2004: MapReduce: Simplified Data Processing on Large Clusters]( http://static.googleusercontent.com/media/research.google.com/en//archive/mapreduce-osdi04.pdf)
|
||||
- mostly replaced by Cloud Dataflow?
|
||||
- [ ] [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)
|
||||
- [ ] [2012: Google's Colossus](https://www.wired.com/2012/07/google-colossus/)
|
||||
- paper not available
|
||||
- [ ] 2012: AddressSanitizer: A Fast Address Sanity Checker:
|
||||
- [paper](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/37752.pdf)
|
||||
- [video](https://www.usenix.org/conference/atc12/technical-sessions/presentation/serebryany)
|
||||
- [ ] 2013: Spanner: Google’s Globally-Distributed Database:
|
||||
- [paper](http://static.googleusercontent.com/media/research.google.com/en//archive/spanner-osdi2012.pdf)
|
||||
- [video](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)
|
||||
|
||||
- ### Testing
|
||||
- To cover:
|
||||
- how unit testing works
|
||||
- what are mock objects
|
||||
- what is integration testing
|
||||
- what is dependency injection
|
||||
- [ ] [Agile Software Testing with James Bach (video)](https://www.youtube.com/watch?v=SAhJf36_u5U)
|
||||
- [ ] [Open Lecture by James Bach on Software Testing (video)](https://www.youtube.com/watch?v=ILkT_HV9DVU)
|
||||
- [ ] [Steve Freeman - Test-Driven Development (that’s not what we meant) (video)](https://vimeo.com/83960706)
|
||||
- [slides](http://gotocon.com/dl/goto-berlin-2013/slides/SteveFreeman_TestDrivenDevelopmentThatsNotWhatWeMeant.pdf)
|
||||
- [ ] [TDD is dead. Long live testing.](http://david.heinemeierhansson.com/2014/tdd-is-dead-long-live-testing.html)
|
||||
- [ ] [Is TDD dead? (video)](https://www.youtube.com/watch?v=z9quxZsLcfo)
|
||||
- [ ] [Video series (152 videos) - not all are needed (video)](https://www.youtube.com/watch?v=nzJapzxH_rE&list=PLAwxTw4SYaPkWVHeC_8aSIbSxE_NXI76g)
|
||||
- [ ] [Test-Driven Web Development with Python](http://www.obeythetestinggoat.com/pages/book.html#toc)
|
||||
- [ ] Dependency injection:
|
||||
- [ ] [video](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
|
||||
- in an OS, how it works
|
||||
- can be gleaned from Operating System videos
|
||||
|
||||
- ### Implement system routines
|
||||
- understand what lies beneath the programming APIs you use
|
||||
- can you implement them?
|
||||
|
||||
- ### String searching & manipulations
|
||||
- [ ] [Sedgewick - Suffix Arrays (video)](https://www.youtube.com/watch?v=HKPrVm5FWvg)
|
||||
- [ ] [Sedgewick - Substring Search (videos)](https://www.youtube.com/watch?v=2LvvVFCEIv8&list=PLe-ggMe31CTdAdjXB3lIuf2maubzo9t66&index=5)
|
||||
- [ ] [1. Introduction to Substring Search](https://www.youtube.com/watch?v=2LvvVFCEIv8&list=PLe-ggMe31CTdAdjXB3lIuf2maubzo9t66&index=5)
|
||||
- [ ] [2. Brute-Force Substring Search](https://www.youtube.com/watch?v=CcDXwIGEXYU&list=PLe-ggMe31CTdAdjXB3lIuf2maubzo9t66&index=4)
|
||||
- [ ] [3. Knuth-Morris Pratt](https://www.youtube.com/watch?v=n-7n-FDEWzc&index=3&list=PLe-ggMe31CTdAdjXB3lIuf2maubzo9t66)
|
||||
- [ ] [4. Boyer-Moore](https://www.youtube.com/watch?v=fI7Ch6pZXfM&list=PLe-ggMe31CTdAdjXB3lIuf2maubzo9t66&index=2)
|
||||
- [ ] [5. Rabin-Karp](https://www.youtube.com/watch?v=QzI0p6zDjK4&index=1&list=PLe-ggMe31CTdAdjXB3lIuf2maubzo9t66)
|
||||
- [ ] [Search pattern in text (video)](https://www.coursera.org/learn/data-structures/lecture/tAfHI/search-pattern-in-text)
|
||||
|
||||
If you need more detail on this subject, see "String Matching" section in [Additional Detail on Some Subjects](#additional-detail-on-some-subjects)
|
||||
|
||||
---
|
||||
|
||||
## Final Review
|
||||
|
|
@ -1678,6 +1597,115 @@ You're never really done.
|
|||
- ### Augmented Data Structures
|
||||
- [ ] [CS 61B Lecture 39: Augmenting Data Structures](https://youtu.be/zksIj9O8_jc?list=PL4BBB74C7D2A1049C&t=950)
|
||||
|
||||
- ### Tries
|
||||
- Note there are different kinds of tries. Some have prefixes, some don't, and some use string instead of bits
|
||||
to track the path.
|
||||
- I read through code, but will not implement.
|
||||
- [ ] [Sedgewick - Tries (3 videos)](https://www.youtube.com/playlist?list=PLe-ggMe31CTe9IyG9MB8vt5xUJeYgOYRQ)
|
||||
- [ ] [1. R Way Tries](https://www.youtube.com/watch?v=buq2bn8x3Vo&index=3&list=PLe-ggMe31CTe9IyG9MB8vt5xUJeYgOYRQ)
|
||||
- [ ] [2. Ternary Search Tries](https://www.youtube.com/watch?v=LelV-kkYMIg&index=2&list=PLe-ggMe31CTe9IyG9MB8vt5xUJeYgOYRQ)
|
||||
- [ ] [3. Character Based Operations](https://www.youtube.com/watch?v=00YaFPcC65g&list=PLe-ggMe31CTe9IyG9MB8vt5xUJeYgOYRQ&index=1)
|
||||
- [ ] [Notes on Data Structures and Programming Techniques](http://www.cs.yale.edu/homes/aspnes/classes/223/notes.html#Tries)
|
||||
- [ ] Short course videos:
|
||||
- [ ] [Introduction To Tries (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/08Xyf/core-introduction-to-tries)
|
||||
- [ ] [Performance Of Tries (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/PvlZW/core-performance-of-tries)
|
||||
- [ ] [Implementing A Trie (video)](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/data-science/data-science-tutorials/using-tries/)
|
||||
- [ ] [Stanford Lecture (real world use case) (video)](https://www.youtube.com/watch?v=TJ8SkcUSdbU)
|
||||
- [ ] [MIT, Advanced Data Structures, Strings (can get pretty obscure about halfway through)](https://www.youtube.com/watch?v=NinWEPPrkDQ&index=16&list=PLUl4u3cNGP61hsJNdULdudlRL493b-XZf)
|
||||
|
||||
- ### Balanced search trees
|
||||
- Know 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://www.youtube.com/watch?v=Najzh1rYQTo&index=23&list=PL-XXv-cvA_iAlnI-BQr9hjqADPBtujFJd)
|
||||
- [ ] 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**
|
||||
- these are a translation of a 2-3 tree (see below)
|
||||
- In practice:
|
||||
Red–black trees offer worst-case guarantees for insertion time, deletion time, and search time.
|
||||
Not only does this make them valuable in time-sensitive applications such as real-time applications,
|
||||
but it makes them valuable building blocks in other data structures which provide worst-case guarantees;
|
||||
for example, many data structures used in computational geometry can be based on red–black trees, and
|
||||
the Completely Fair Scheduler used in current Linux kernels uses red–black trees. In the version 8 of Java,
|
||||
the Collection HashMap has been modified such that instead of using a LinkedList to store identical elements with poor
|
||||
hashcodes, a Red-Black tree is used.
|
||||
- [ ] [Aduni - Algorithms - Lecture 4 (link jumps to starting point) (video)](https://youtu.be/1W3x0f_RmUo?list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&t=3871)
|
||||
- [ ] [Aduni - Algorithms - Lecture 5 (video)](https://www.youtube.com/watch?v=hm2GHwyKF1o&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=5)
|
||||
- [ ] [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/data-science/data-science-tutorials/an-introduction-to-binary-search-and-red-black-trees/)
|
||||
|
||||
- [ ] **2-3 search trees**
|
||||
- In practice:
|
||||
2-3 trees have faster inserts at the expense of slower searches (since height is more compared to AVL trees).
|
||||
- You would use 2-3 tree very rarely because its implementation involves different types of nodes. Instead, people use Red Black trees.
|
||||
- [ ] [23-Tree Intuition and Definition (video)](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) (video)](https://www.youtube.com/watch?v=TOb1tuEZ2X4&index=5&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp)
|
||||
|
||||
- [ ] **2-3-4 Trees (aka 2-4 trees)**
|
||||
- In practice:
|
||||
For every 2-4 tree, there are corresponding red–black trees with data elements in the same order. The insertion and deletion
|
||||
operations on 2-4 trees are also equivalent to color-flipping and rotations in red–black trees. This makes 2-4 trees an
|
||||
important tool for understanding the logic behind red–black trees, and this is why many introductory algorithm texts introduce
|
||||
2-4 trees just before red–black trees, even though **2-4 trees are not often used in practice**.
|
||||
- [ ] [CS 61B Lecture 26: Balanced Search Trees (video)](https://www.youtube.com/watch?v=zqrqYXkth6Q&index=26&list=PL4BBB74C7D2A1049C)
|
||||
- [ ] [Bottom Up 234-Trees (video)](https://www.youtube.com/watch?v=DQdMYevEyE4&index=4&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6)
|
||||
- [ ] [Top Down 234-Trees (video)](https://www.youtube.com/watch?v=2679VQ26Fp4&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6&index=5)
|
||||
|
||||
- [ ] **N-ary (K-ary, M-ary) trees**
|
||||
- note: the N or K is the branching factor (max branches)
|
||||
- binary trees are a 2-ary tree, with branching factor = 2
|
||||
- 2-3 trees are 3-ary
|
||||
- [ ] [K-Ary Tree](https://en.wikipedia.org/wiki/K-ary_tree)
|
||||
|
||||
- [ ] **B-Trees**
|
||||
- fun fact: it's a mystery, but the B could stand for Boeing, Balanced, or Bayer (co-inventor)
|
||||
- In Practice:
|
||||
B-Trees are widely used in databases. Most modern filesystems use B-trees (or Variants). In addition to
|
||||
its use in databases, the B-tree is also used in filesystems to allow quick random access to an arbitrary
|
||||
block in a particular file. The basic problem is turning the file block i address into a disk block
|
||||
(or perhaps to a cylinder-head-sector) address.
|
||||
- [ ] [B-Tree](https://en.wikipedia.org/wiki/B-tree)
|
||||
- [ ] [Introduction to B-Trees (video)](https://www.youtube.com/watch?v=I22wEC1tTGo&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6&index=6)
|
||||
- [ ] [B-Tree Definition and Insertion (video)](https://www.youtube.com/watch?v=s3bCdZGrgpA&index=7&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6)
|
||||
- [ ] [B-Tree Deletion (video)](https://www.youtube.com/watch?v=svfnVhJOfMc&index=8&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6)
|
||||
- [ ] [MIT 6.851 - Memory Hierarchy Models (video)](https://www.youtube.com/watch?v=V3omVLzI0WE&index=7&list=PLUl4u3cNGP61hsJNdULdudlRL493b-XZf)
|
||||
- covers cache-oblivious B-Trees, very interesting data structures
|
||||
- the first 37 minutes are very technical, may be skipped (B is block size, cache line size)
|
||||
|
||||
|
||||
- ### k-D Trees
|
||||
- great for finding number of points in a rectangle or higher dimension object
|
||||
- a good fit for k-nearest neighbors
|
||||
|
|
|
|||
Loading…
Reference in New Issue