Class Lectures: Mon, Wed 5:30 PM - 6:45 PM, HN C107 Professor Saad Mneimneh, HN 1090L Office hours: Wed, Thu 2:30 - 3:30

Textbooks
Introduction to Algorithms, CLRS
Topics to be covered: Insertion sort, merge sort, asymptotic notation, Strassen's algorithm, Growth of functions, O notation and others, solving recurrences, recursive tree method, substitution method, Master method, Quicksort, randomized algorithms, probabilistic analysis, indicator random variables and expectations, heapsort, sorting in linear time, median and order statistics, hash tables, binary search trees, red black trees, augmenting data structures, dynamic programming, greedy algorithms, amortized analysis, disjoint sets data structure, minimum spanning trees, Krusgal and Prim algorithm, short path algorithms, Bellman-Ford, Dijkstra, all pairs shortest path, Floyd Warshall, difference constraints, BFS, DFS, topological sort, connected components.

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Lectures (will follow these closely from previous offering)
(Sections are based on 3rd Edition)
- Lecture 1: Insertion sort, pseudocode. Section 2.1 Insertion sort
- Lecture 2: Analysis, asymptotic notation, merge sort, Strassen's alg. Sections 2.2 Analyzing algorithms, 2.3 Designing algorithms, 4.2 Strassen's algorithm for matrix multiplication.
- Lecture 3: Growth of functions, Chapter 3
- Lecture 4: Solving recurrence equations, recursive tree, substitution method, Master method. Sections 4.3, 4.4, and 4.5.
- Lecture 5: Quicksort, Sections 7.1, 7.2, 7.3, 7.4.1, and Ex 7-2.
- Lecture 6: Randomized algorithms and indicator R.V. Sections 5.1, 5.2, 5.3, and 7.4.2.
- Lecture 7: Mergesort and priority queues using heaps. Chapter 6.
- Lecture 8: Sorting in linear time, counting sort, radix sort, and bucket sort. Chapter 8.
- Lecture 9: Order statistics in linear time, Chapter 9, Sections 9.1, 9.2, and 9.3.
- Lecture 10. Hashing. Chapter 11, Sections 11.2, 11.3, and Pr 11-4.
- Lecture 11 Continue with Hashing, open addressing, perfect hashing. Chapter 11, Section 11.4 and 11.5.
- Lecture 12 Binary search trees, chapter 12.
- Lecture 13 Red-black trees and skip lists, Chpater 13, Sections 1, 2, and 3, focus on the 3 cases for insertion.
- Lecture 14 Augmenting red-black trees, interval trees. Chapter 14.
- Lecture 15 Dynamic programming, Chapter 15 sections about LCS and optimal BST.
- Lecture 16 Greedy algorithms. Chapter 16 Sections 1 and 2. Chapter 23 Section 1 and Prim's alg. in Section 2.
- Lecture 17 Krusgal's alg. Disjoint sets, Amortized time analysis, Chapter 23 Section 23.2, Chapter 21 Sections 21.1, 21.2, Chapter 17, Sections 17.1
- Lecture 18 Continue with Amortized Analysis, Chapter 17, Sections 17.2, 17.3, 17.4.
- Lecture 19 BFS and single source shortest path, Bellman-Ford, Dijkstra.

Homework
Homework 1 Due 2/14/2024
Homework 2 Due 2/22/2024
Homework 3 Due 2/29/2024
Homework 4 Due 3/8/2024
Homework 5 Due 3/22/2024
Homework 6 Due 3/29/2024
Homework 7 Due 4/12/2024

Grading policy
- Homework 20%
- Test 1 20%
- Test 2 20%
- Final 30%
- Report 10%