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John Washam 2016-07-10 21:27:55 -07:00
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@ -439,40 +439,53 @@ Then test it out on a computer to make sure it's not buggy from syntax.
- [x] 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).
- [ ] **Balanced binary trees**
- [ ] **Balanced search trees**
- Know least one type of balanced binary tree (and know how it's implemented):
- [ ] **2-3 search trees, B-Trees**
- fun fact: B could stand for Boeing, Balanced, or Bayer (co-inventor)
- [ ] Recitation: 2-3 Trees and B-Trees: https://www.youtube.com/watch?v=TOb1tuEZ2X4&index=5&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp
- [ ] **2-3-4 Trees**
- [ ] CS 61B Lecture 26: Balanced Search Trees: https://www.youtube.com/watch?v=zqrqYXkth6Q&index=26&list=PL4BBB74C7D2A1049C
- [x] **AVL trees**
- [x] MIT AVL Trees / AVL Sort: 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
- [ ] **Splay trees**
- [ ] CS 61B: Splay Trees: https://www.youtube.com/watch?v=Najzh1rYQTo&index=23&list=PL-XXv-cvA_iAlnI-BQr9hjqADPBtujFJd
- [ ] MIT Lecture: Splay Trees: https://www.youtube.com/watch?v=QnPl_Y6EqMo
- [x] **Splay trees**
- [x] CS 61B: Splay Trees: https://www.youtube.com/watch?v=Najzh1rYQTo&index=23&list=PL-XXv-cvA_iAlnI-BQr9hjqADPBtujFJd
- [x] MIT Lecture: Splay Trees:
- Gets very mathy, but watch the last 10 minutes for sure.
- https://www.youtube.com/watch?v=QnPl_Y6EqMo
- [x] **2-3-4 Trees**
- [x] CS 61B Lecture 26: Balanced Search Trees: https://www.youtube.com/watch?v=zqrqYXkth6Q&index=26&list=PL4BBB74C7D2A1049C
- [x] **2-3 search trees**
- [x] 2-3 Trees (student recitation): https://www.youtube.com/watch?v=TOb1tuEZ2X4&index=5&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp
- [ ] **Red/black trees**
- [ ] MIT: https://www.youtube.com/watch?v=gDYn5TfcUVs
- [ ] Aduni - Algorithms - Lecture 4
link jumps to starting point:
https://youtu.be/1W3x0f_RmUo?list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&t=3871
- [ ] Aduni - Algorithms - Lecture 5: https://www.youtube.com/watch?v=hm2GHwyKF1o&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=5
- [ ] **B-Trees**
- fun fact: B could stand for Boeing, Balanced, or Bayer (co-inventor)
- [ ] **Skip lists**
- [ ] MIT: Randomization: Skip Lists: https://www.youtube.com/watch?v=2g9OSRKJuzM&index=10&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp
- [ ] **Treap**
- [ ] ?
- [ ] **N-ary trees**
- https://en.wikipedia.org/wiki/K-ary_tree
- [ ] 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
- [ ] 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
- [ ] **Disjoint Sets:**
- [ ] https://en.wikipedia.org/wiki/Disjoint-set_data_structure
- [ ] UCB: https://www.youtube.com/watch?v=wSPAjGfDl7Q&list=PL4BBB74C7D2A1049C&index=31
- [ ] UCB 61B - Disjoint Sets; Sorting & selection: https://www.youtube.com/watch?v=MAEGXTwmUsI&list=PL-XXv-cvA_iAlnI-BQr9hjqADPBtujFJd&index=21
- [ ] 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
@ -635,7 +648,7 @@ You'll get more graph practice in Skiena's book (see Books section below) and th
- performance analysis and optimization
- [ ] **Familiarize yourself with a unix-based code editor: emacs & vi(m)**
- suggested by Yegge
- suggested by Yegge, from an old Amazon recruiting post
- vi(m):
- https://www.youtube.com/watch?v=5givLEMcINQ&index=1&list=PL13bz4SHGmRxlZVmWQ9DvXo1fEg4UdGkr
- set of 4:
@ -643,6 +656,7 @@ You'll get more graph practice in Skiena's book (see Books section below) and th
- https://www.youtube.com/watch?v=F3OO7ZIOaJE
- https://www.youtube.com/watch?v=ZYEccA_nMaI
- https://www.youtube.com/watch?v=1lYD5gwgZIA
- http://www.cs.yale.edu/homes/aspnes/classes/223/notes.html#Using_Vi_instead_of_Emacs
- emacs:
- https://www.youtube.com/watch?v=hbmV1bnQ-i0
- set of 3:
@ -650,14 +664,19 @@ You'll get more graph practice in Skiena's book (see Books section below) and th
- https://www.youtube.com/watch?v=XWpsRupJ4II
- https://www.youtube.com/watch?v=paSgzPso-yc
- https://www.youtube.com/watch?v=JWD1Fpdd4Pc
- http://www.cs.yale.edu/homes/aspnes/classes/223/notes.html#Writing_C_programs_with_Emacs
- [ ] **Be able to use unix command line tools:**
- suggested by Yegge
- bash
- grep
- sed
- awk
- curl or wget
- suggested by Yegge, from an old Amazon recruiting post. I filled in the list below from good tools.
- [ ] bash
- [ ] cat
- [ ] grep
- [ ] sed
- [ ] awk
- [ ] curl or wget
- [ ] sort
- [ ] tr
- [ ] uniq
- [ ] **Testing**
- how unit testing works