Lectures and Recitations
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Introduction and Document Distance
Lecture 1, Introduction and Document Distance
- Document Distance (docdist{1,2,3,4}.py)
- Readings: CLRS Chapters 1,2,3
Recitation 1
- (R01, R02)
docdist_profiling.py
- (R06) Recitation01 Notes
Lecture 2, Document Distance, Mergesort
- Document Distance (docdist{5,6}.py)
-
mergesort.py
code from class - Readings:
- CLRS Chapter 11, Sections 1-2; CLRS Chapter 4
- Python Cost Model
Recitation 2 : maximum sum contiguous subarray problem
- Jon Bentley's column on the maximum sum contiguous vector problem discussed in class
- (R01, R02) Rec 02 warmup
- (R01, R02)
maxsumsubarray.py
- (R06) Recitation02 Notes
Binary Search Trees
Lecture 3, Binary Search Trees
-
runway.py
code from class - Readings: CLRS Chapter 10; Chapter 12, Sections 1-3
Recitation 3
- (R01, R02) Rec 03
- (R01, R02)
BSTobjects.py
implements BSTs as python objects -
BSTlists.py
implementation extending the one shown in lecture - (R06) Recitation03 Notes
Lecture 4 : AVL trees (Balanced BSTs)
Recitation 4
- AVL applet
- Another AVL applet
- (R03, R04)
AVL template
- (R01, R02) Rec 04
- (R06) Recitation04 Notes
Hashing
Lecture 5 : Hashing I
Readings: CLRS 11.1-11.3
Recitation 5
- (R01, R02) Rec 05
Lecture 6 : Hashing II
Readings: CLRS 17, 32.2
Recitation 6
- (R01, R02, R05) Rec 06
Lecture 7 : Hashing III
Readings: CLRS 11.4, 11.3.3, 11.5
Recitation 7
- short cuckoo hashing reference
- (R01, R02) Rec 07
Sorting
Lecture 8 : Insertion, Merge, and Heap Sort
Recitation 8
- (R01, R02)
- (R06) Recitation08 Notes
Lecture 9 : more heaps(heapsort, building), priority queues
Recitation 9
- (R1, R2)
- notes
- merging k-lists code (i have not verified the validity of this code)
- merging k-lists in more depth
Lecture 10 : Decision tree - lower bounds on sorting, counting sort
Recitation 10
- (R1, R2)