Lectures

Class lectures:
Tuesdays, Thursdays 2:00pm-3:20pm HSS 1330

The purpose of lectures is to introduce the basic material we will be covering in this course. You will be responsible for this material on the exams, and you will need to know it to do the programming assignments.

The only reason to come to lecture is to learn something about this material. If you're not interested in that, don't waste your time. The basic rule is: Listen or leave.

The lecture notes below are in HTML and PDF format. (I revise my lecture notes every quarter, and so they may not be available here much in advance of the lecture itself. If you need a PDF reader for your own browser, you can download Acrobat Reader for free from Adobe .)

Lecture 1 Thu Sep 22
Introduction; Structure and requirements of the course; Overview of trees and their properties.

Lecture 2 Tue Sep 27
The C++ programming language; comparison of C++ and Java; introduction to OO programming in C++. (Reading: Weiss Ch 1)

Lecture 3 Thu Sep 29
Binary search trees; basic operations on BST's; BST's, C++ iterators, and the BST successor function. (Reading: Weiss Ch. 4)

Lecture 4 Tue Oct 04
Analysis of binary search trees; balance; AVL trees and AVL rotations; AVL insertion. (Reading: Weiss Ch. 4)

Lecture 5 Thu Oct 06
Treaps; Find, insert, delete, split, and join in treaps; Randomized search trees; Analysis of randomized search trees. (Reading: Aragon and Seidel paper; Weiss Ch. 12)

Lecture 6 Tue Oct 11
Random number generation; Randomized data structures; Skip lists; Analysis of skip lists. (Reading: Pugh paper; Weiss Ch. 10)

Lecture 7 Thu Oct 13
Red-black trees; Analysis of red-black trees; operations on red-black trees. (Reading: Weiss Ch. 12)

Lecture 8 Tue Oct 18
Trees for representation; Tries, decision and classification trees, discrimination nets; alphabet tries; Huffman coding. (Reading: Weiss Ch. 10)

Lecture 9 Thu Oct 20
Analysis of Huffman coding; Priority queues; Heaps; Dynamic data and array representations of Huffman tries. (Reading: Weiss Ch. 6 and Ch. 10)

Lecture 10 Tue Oct 25
I/O in C++; C++ standard library I/O classes; Binary and text file I/O; Buffering; Bitwise I/O. (Reading: C++ I/O documentation)

Midterm exam Thu Oct 27

Lecture 11 Tue Nov 01
Intro to Graphs; vertices, edges, paths, cycles; Sparse and dense graphs; Adjacency matrices and adjacency lists. (Reading: Weiss, Ch. 9)

Lecture 12 Thu Nov 03
Algorithms on graphs; breadth-first, depth-first search; shortest path in unweighted graphs; greedy algorithms; Djikstra's algorithm for shortest paths in weighted graphs. (Reading: Weiss, Ch. 9, Ch. 10)

Lecture 13 Tue Nov 08
Connectedness in graphs; spanning trees; Prim's and Kruskal's algorithms for finding minimum cost spanning trees; disjoint subset data structures and union-find; Analysis of graph algorithms and NP-completeness. (Reading: Weiss, Ch. 8, Ch. 9)

Lecture 14 Thu Nov 10
Applications of disjoint subsets; union-by-height and union-by-size; Find with path compression; Amortized cost analysis. (Reading: Weiss, Ch. 8)

Lecture 15 Tue Nov 15
Radix search; digital search trees, multiway tries, ternary tries and their properties.

Lecture 16 Thu Nov 17
Hashing; hash table and hash function design; Hash functions for integers and strings; Open addressing and separate chaining collision resolution strategies; Analysis of hashing. (Reading: Weiss, Ch. 5)

Lecture 17 Tue Nov 22
Time costs in a memory hierarchy; B-trees; B-tree find, insert, delete; 2-3 trees; Analysis of B-trees. (Reading: Weiss, Ch. 4)

University holiday Thu Nov 24

Lecture 18 Tue Nov 29
Self-organizing data structures; self-organizing lists; Splay trees; Spatial data structures; K-D trees. (Reading: Weiss, Ch. 4 and Ch. 12)

Lecture 19 Thu Dec 01
Final review.

Lecture 1	Thu Sep 22	Introduction; Structure and requirements of the course; Overview of trees and their properties.
Lecture 2	Tue Sep 27	The C++ programming language; comparison of C++ and Java; introduction to OO programming in C++. (Reading: Weiss Ch 1)
Lecture 3	Thu Sep 29	Binary search trees; basic operations on BST's; BST's, C++ iterators, and the BST successor function. (Reading: Weiss Ch. 4)
Lecture 4	Tue Oct 04	Analysis of binary search trees; balance; AVL trees and AVL rotations; AVL insertion. (Reading: Weiss Ch. 4)
Lecture 5	Thu Oct 06	Treaps; Find, insert, delete, split, and join in treaps; Randomized search trees; Analysis of randomized search trees. (Reading: Aragon and Seidel paper; Weiss Ch. 12)
Lecture 6	Tue Oct 11	Random number generation; Randomized data structures; Skip lists; Analysis of skip lists. (Reading: Pugh paper; Weiss Ch. 10)
Lecture 7	Thu Oct 13	Red-black trees; Analysis of red-black trees; operations on red-black trees. (Reading: Weiss Ch. 12)
Lecture 8	Tue Oct 18	Trees for representation; Tries, decision and classification trees, discrimination nets; alphabet tries; Huffman coding. (Reading: Weiss Ch. 10)
Lecture 9	Thu Oct 20	Analysis of Huffman coding; Priority queues; Heaps; Dynamic data and array representations of Huffman tries. (Reading: Weiss Ch. 6 and Ch. 10)
Lecture 10	Tue Oct 25	I/O in C++; C++ standard library I/O classes; Binary and text file I/O; Buffering; Bitwise I/O. (Reading: C++ I/O documentation)
Midterm exam	Thu Oct 27
Lecture 11	Tue Nov 01	Intro to Graphs; vertices, edges, paths, cycles; Sparse and dense graphs; Adjacency matrices and adjacency lists. (Reading: Weiss, Ch. 9)
Lecture 12	Thu Nov 03	Algorithms on graphs; breadth-first, depth-first search; shortest path in unweighted graphs; greedy algorithms; Djikstra's algorithm for shortest paths in weighted graphs. (Reading: Weiss, Ch. 9, Ch. 10)
Lecture 13	Tue Nov 08	Connectedness in graphs; spanning trees; Prim's and Kruskal's algorithms for finding minimum cost spanning trees; disjoint subset data structures and union-find; Analysis of graph algorithms and NP-completeness. (Reading: Weiss, Ch. 8, Ch. 9)
Lecture 14	Thu Nov 10	Applications of disjoint subsets; union-by-height and union-by-size; Find with path compression; Amortized cost analysis. (Reading: Weiss, Ch. 8)
Lecture 15	Tue Nov 15	Radix search; digital search trees, multiway tries, ternary tries and their properties.
Lecture 16	Thu Nov 17	Hashing; hash table and hash function design; Hash functions for integers and strings; Open addressing and separate chaining collision resolution strategies; Analysis of hashing. (Reading: Weiss, Ch. 5)
Lecture 17	Tue Nov 22	Time costs in a memory hierarchy; B-trees; B-tree find, insert, delete; 2-3 trees; Analysis of B-trees. (Reading: Weiss, Ch. 4)
University holiday	Thu Nov 24
Lecture 18	Tue Nov 29	Self-organizing data structures; self-organizing lists; Splay trees; Spatial data structures; K-D trees. (Reading: Weiss, Ch. 4 and Ch. 12)
Lecture 19	Thu Dec 01	Final review.