MC9223 DESIGN AND ANALYSIS OF ALGORITHMS SYLLABUS | ANNA UNIVERSITY MCA 2nd SEMESTER SYLLABUS REGULATION 2009 2011 2012-2013 BELOW IS THE ANNA UNIVERSITY SECOND SEMESTER MCA MASTER OF COMPUTER APPLICATIONS DEPARTMENT SYLLABUS, TEXTBOOKS, REFERENCE BOOKS,EXAM PORTIONS,QUESTION BANK,PREVIOUS YEAR QUESTION PAPERS,MODEL QUESTION PAPERS, CLASS NOTES, IMPORTANT 2 MARKS, 8 MARKS, 16 MARKS TOPICS. IT IS APPLICABLE FOR ALL STUDENTS ADMITTED IN THE YEAR 2011 2012-2013 (ANNA UNIVERSITY CHENNAI,TRICHY,MADURAI,TIRUNELVELI,COIMBATORE), 2009 REGULATION OF ANNA UNIVERSITY CHENNAI AND STUDENTS ADMITTED IN ANNA UNIVERSITY CHENNAI DURING 2009
MC 9223 DESIGN AND ANALYSIS OF ALGORITHMS LT P C
3 1 0 4
UNIT I INTRODUCTION 10
Fundamentals of algorithmic problem solving – Important problem types –
Fundamentals of the analysis of algorithm efficiency – analysis frame work –
Asymptotic notations – Mathematical analysis for recursive and non-recursive
algorithms.
UNIT II DIVIDE AND CONQUER METHOD AND GREEDY METHOD 12
Divide and conquer methodology – Merge sort – Quick sort – Binary search – Binary
tree traversal – Multiplication of large integers – Strassen’s matrix multiplication –
Greedy method – Prim’s algorithm – Kruskal’s algorithm – Dijkstra’s algorithm.
UNIT III DYNAMIC PROGRAMMING 12
Computing a binomial coefficient – Warshall’s and Floyd’ algorithm – Optimal binary
search tree – Knapsack problem – Memory functions.
6
UNIT IV BACKTRACKING AND BRANCH AND BOUND 14
Backtracking – N-Queens problem – Hamiltonian circuit problem – Subset sum problem
– Branch and bound – Assignment problem – Knapsack problem – Traveling
salesman problem.
UNIT V NP-HARD AND NP-COMPLETE PROBLEMS 12
P & NP problems – NP-complete problems – Approximation algorithms for NP-hard
problems – Traveling salesman problem – Knapsack problem.
L : 45 T : 15 TOTAL : 60 PERIODS
REFERENCES:
1. Anany Levitin “Introduction to the Design and Analysis of Algorithms” Pearson
Education 2003.
2. Thomas H.Cormen, Charles E.Leiserson, Ronald L.Rivest, “Introduction to
algorithms” Prentice Hall 1990.
MC 9223 DESIGN AND ANALYSIS OF ALGORITHMS LT P C
3 1 0 4
UNIT I INTRODUCTION 10
Fundamentals of algorithmic problem solving – Important problem types –
Fundamentals of the analysis of algorithm efficiency – analysis frame work –
Asymptotic notations – Mathematical analysis for recursive and non-recursive
algorithms.
UNIT II DIVIDE AND CONQUER METHOD AND GREEDY METHOD 12
Divide and conquer methodology – Merge sort – Quick sort – Binary search – Binary
tree traversal – Multiplication of large integers – Strassen’s matrix multiplication –
Greedy method – Prim’s algorithm – Kruskal’s algorithm – Dijkstra’s algorithm.
UNIT III DYNAMIC PROGRAMMING 12
Computing a binomial coefficient – Warshall’s and Floyd’ algorithm – Optimal binary
search tree – Knapsack problem – Memory functions.
6
UNIT IV BACKTRACKING AND BRANCH AND BOUND 14
Backtracking – N-Queens problem – Hamiltonian circuit problem – Subset sum problem
– Branch and bound – Assignment problem – Knapsack problem – Traveling
salesman problem.
UNIT V NP-HARD AND NP-COMPLETE PROBLEMS 12
P & NP problems – NP-complete problems – Approximation algorithms for NP-hard
problems – Traveling salesman problem – Knapsack problem.
L : 45 T : 15 TOTAL : 60 PERIODS
REFERENCES:
1. Anany Levitin “Introduction to the Design and Analysis of Algorithms” Pearson
Education 2003.
2. Thomas H.Cormen, Charles E.Leiserson, Ronald L.Rivest, “Introduction to
algorithms” Prentice Hall 1990.
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