Updating the list of what you need to know (for entry-level engineers) based on recent info.

README.md

@@ -13,6 +13,9 @@ There are extra items I added at the bottom that may come up in the interview or
 Steve Yegge's "[Get that job at Google](http://steve-yegge.blogspot.com/2008/03/get-that-job-at-google.html)" and are reflected
 sometimes word-for-word in Google's coaching notes.
 
+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.
+[Read more here](https://googleyasheck.com/what-you-need-to-know-for-your-google-interview-and-what-you-dont/).
+
 ---
 
 ## Table of Contents
@@ -46,11 +49,20 @@ sometimes word-for-word in Google's coaching notes.
     - [Trees - Notes & Background](#trees---notes--background)
     - [Binary search trees: BSTs](#binary-search-trees-bsts)
     - [Heap / Priority Queue / Binary Heap](#heap--priority-queue--binary-heap)
-    - [Tries](#tries)
-    - [Balanced search trees](#balanced-search-trees)
-    - [N-ary (K-ary, M-ary) trees](#n-ary-k-ary-m-ary-trees)
+    - balanced search trees (general concept, not details)
+    - traversals: preorder, inorder, postorder, BFS, DFS
 - [Sorting](#sorting)
+    - selection
+    - insertion
+    - heapsort
+    - quicksort
+    - merge sort
 - [Graphs](#graphs)
+    - directed
+    - undirected
+    - adjacency matrix
+    - adjacency list
+    - traversals: BFS, DFS
 - [Even More Knowledge](#even-more-knowledge)
     - [Recursion](#recursion)
     - [Dynamic Programming](#dynamic-programming)
@@ -58,12 +70,12 @@ sometimes word-for-word in Google's coaching notes.
     - [NP, NP-Complete and Approximation Algorithms](#np-np-complete-and-approximation-algorithms)
     - [Caches](#caches)
     - [Processes and Threads](#processes-and-threads)
-    - [System Design, Scalability, Data Handling](#system-design-scalability-data-handling)
     - [Papers](#papers)
     - [Testing](#testing)
     - [Scheduling](#scheduling)
     - [Implement system routines](#implement-system-routines)
     - [String searching & manipulations](#string-searching--manipulations)
+- [System Design, Scalability, Data Handling](#system-design-scalability-data-handling) (if you have 4+ years experience)
 - [Final Review](#final-review)
 - [Coding Question Practice](#coding-question-practice)
 - [Coding exercises/challenges](#coding-exerciseschallenges)
@@ -88,7 +100,7 @@ sometimes word-for-word in Google's coaching notes.
     - [Entropy](#entropy)
     - [Cryptography](#cryptography)
     - [Compression](#compression)
-    - [Networking](#networking)
+    - [Networking](#networking) (if you have networking experience, expect questions)
     - [Computer Security](#computer-security)
     - [Garbage collection](#garbage-collection)
     - [Parallel Programming](#parallel-programming)
@@ -100,6 +112,16 @@ sometimes word-for-word in Google's coaching notes.
     - [Locality-Sensitive Hashing](#locality-sensitive-hashing)
     - [van Emde Boas Trees](#van-emde-boas-trees)
     - [Augmented Data Structures](#augmented-data-structures)
+    - [Tries](#tries)
+    - [N-ary (K-ary, M-ary) trees](#n-ary-k-ary-m-ary-trees)
+    - [Balanced search trees](#balanced-search-trees)
+        - AVL trees
+        - Splay trees
+        - Red/black trees
+        - 2-3 search trees
+        - 2-3-4 Trees (aka 2-4 trees)
+        - N-ary (K-ary, M-ary) trees
+        - B-Trees
     - [k-D Trees](#k-d-trees)
     - [Skip lists](#skip-lists)
     - [Network Flows](#network-flows)
@@ -645,113 +667,6 @@ Write code on a whiteboard or paper, not a computer. Test with some sample input
         - [ ] heap_sort() - take an unsorted array and turn it into a sorted array in-place using a max heap
             - note: using a min heap instead would save operations, but double the space needed (cannot do in-place).
 
-- ### 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)
-
-    - [ ] **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)
-
-    - [ ] **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)
-
-    - [ ] **Red/black trees**
-        - 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/)
-
-- ### 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)
-
 ## Sorting
 
 - [ ] Notes:
@@ -1002,9 +917,78 @@ You'll get more graph practice in Skiena's book (see Books section below) and th
         - [ ] [Keynote David Beazley - Topics of Interest (Python Asyncio)](https://www.youtube.com/watch?v=ZzfHjytDceU)
         - [ ] [Mutex in Python](https://www.youtube.com/watch?v=0zaPs8OtyKY)
 
+- ### 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)
+
+---
 
     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