# Course Outline-Design and Analysis of Algorithms-Handout, Exercises for Design and Analysis of Algorithms. Allahabad University

## Design and Analysis of Algorithms

Description: This is course outline for Design and Analysis of Algorithms. Its instructer name is Amar Singh Rathore at Allahabad University. It includes: Course, Outline, Objectives, Mathematic, Analysis, Non-recursive, Recursive, Algorithms, Divide, Conquer, Sort, Analysis
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Course No.: CS3163
Course Title: Design & Analysis of Algorithms
Objectives:
The objective of this course is to develop fundamental skills in designing and
analyzing algorithms. Algorithm design has grown into a mature discipline with
standard 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 concrete
examples. 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, graph
algorithms, scheduling, geometric and numeric algorithms etc. This course will focus
on the design and analysis of algorithms, although some implementation issues will
also be considered.
Course Pre-Requisite/Co-Requisite:
Data Structures
Discrete Mathematics
Reference Books/Materials:
1. Introduction to the Design & Analysis of Algorithms
By Anany Levitin
2. Foundations of Algorithms
By Richard E. Neapolitan, Kumarss Naimipour, Northeastern Illinois
University
2. Cormen, Leiserson and Rivest, Introduction to Algorithms, MIT Press,
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 Notations
2
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. Strassen’s Matrix Multiplication,
ii. Multiplication of large Integers
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6
i. Class Test 1
ii. Sorting in Linear Time, Radix Sort
7
i. Sorting in Linear Time, Radix Sort
ii. Dynamic Programming
8
i. Binomial Coefficient
ii. Chained matrix Multiplications
9
MidTerm
10
i. Floyd’s 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. Dijkstra’s Algorthms
13
i. Scheduling
ii. Greedy Approach Versus Dynamic Programming
14
i. Knapsack Problem
ii. 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 Problem
18
i. Introduction to Computational Complexity and Intractability
ii. Theory of NP
Evaluation Criteria:
Mid term
20%
Class Tests & Quizes
15%
Final
40%
Project
10%
Assignments & Presentations
15%
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