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M.A.J.U.

Mohammad Ali Jinnah University

Islamabad CampusCourse No.: CS3163

Course Title: Design & Analysis of Algorithms

Instructor: Omara Abdul Hamid

Email Address: omara@jinnah.edu.pk

Term (Semester): Spring 2011

Duration (in weeks): 16

Objectives:

The objective of this course is to develop fundamental skills in designing and

analyzing algorithms. Algorithm design has grown into a mature discipline withstandard and powerful techniques and a sound mathematical basis. This course

presents some fundamental concepts involved in the design and analysis of computer

algorithms. We will learn the basic algorithm design techniques through concreteexamples. The algorithms discussed concern classical problems in computer science

and real problems that arise frequently in computer applications -- chosen from a

variety of domains including sorting, searching, selection, string matching, graphalgorithms, scheduling, geometric and numeric algorithms etc. This course will focus

on the design and analysis of algorithms, although some implementation issues willalso be considered.

Course Pre-Requisite/Co-Requisite:

Data StructuresDiscrete Mathematics

Reference Books/Materials:

1. Introduction to the Design & Analysis of Algorithms

By Anany Levitin

2. Foundations of AlgorithmsBy Richard E. Neapolitan, Kumarss Naimipour, Northeastern Illinois

University

2. Cormen, Leiserson and Rivest, Introduction to Algorithms, MIT Press,

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Lecture Schedule (weekly):

WEEK# TOPICS

1 i. Introduction of the course, Objectives, Motivation, Course Overview

ii. Analysis of Algorithms, Time Complexity Analysis, Space

Complexity Analysis, Asymptotic Notations2 i. Mathematical Analysis of Non-Recursive Algorithms.

ii. Analysis of recursive Algorithms

3 i. Analysis of recursive Algorithms

ii. Divide & Conquer

4 i. Merge Sort Analysis.

ii. Quick Sort Analysis

5 i. Strassens Matrix Multiplication,

ii. Multiplication of large Integers

6 i. Class Test 1

ii. Sorting in Linear Time, Radix Sort7 i. Sorting in Linear Time, Radix Sort

ii. Dynamic Programming

8 i. Binomial Coefficientii. Chained matrix Multiplications

9 MidTerm

10 i. Floyds Algorithm for Shortest Paths

ii. Optimal Binary Search

11 i. The Travelling Sales Person Problem

ii. Introduction to Greedy Approach

12 i. Minimum Spanning Trees

ii. Dijkstras Algorthms

13 i. Schedulingii. Greedy Approach Versus Dynamic Programming

14 i. Knapsack Problemii. Backtracking Technique

15 i. Class Test 2

ii. N-Queen Problem

16 iii. N-Queen Problem

iv. Graph Coloring

17 i. The Hamiltonian Circuits Problem.

ii. The Sum-of-Subsets Problem18 i. Introduction to Computational Complexity and Intractability

ii. Theory of NP

Evaluation Criteria:

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Mid term 20%

Class Tests 20%

Final 20%

Quizzes (unannounced) 10%

Project 10%

Lab Test (unannounced) 10%

Assignments (individual) 10%