CS8451 DAA Syllabus
Anna University Regulation 2017 CSE CS8451 DAA Syllabus for all 5 units are provided below. Download link for CSE 4th SEM CS8451 DESIGN AND ANALYSIS OF ALGORITHMS Engineering Syllabus is listed down for students to make perfect utilization and score maximum marks with our study materials.
Anna University Regulation 2017 Computer Science Engineering (CSE) 4th SEM CS8451 DESIGN AND ANALYSIS OF ALGORITHMS Engineering Syllabus
CS8451 DESIGN AND ANALYSIS OF ALGORITHMS
OBJECTIVES:
To understand and apply the algorithm analysis techniques.
To critically analyze the efficiency of alternative algorithmic solutions for the same problem
To understand different algorithm design techniques.
To understand the limitations of Algorithmic power.
UNIT I INTRODUCTION
Notion of an Algorithm – Fundamentals of Algorithmic Problem Solving – Important Problem Types
– Fundamentals of the Analysis of Algorithmic Efficiency –Asymptotic Notations and their properties. Analysis Framework – Empirical analysis – Mathematical analysis for Recursive and Non-recursive algorithms – Visualization
UNIT II BRUTE FORCE AND DIVIDE-AND-CONQUER
Brute Force – Computing an– String Matching – Closest-Pair and Convex-Hull Problems -Exhaustive Search – Travelling Salesman Problem – Knapsack Problem – Assignment problem.Divide and Conquer Methodology – Binary Search – Merge sort – Quick sort – Heap Sort -Multiplication of Large Integers – Closest-Pair and Convex – Hull Problems.
UNIT III DYNAMIC PROGRAMMING AND GREEDY TECHNIQUE
Dynamic programming – Principle of optimality – Coin changing problem, Computing a Binomial Coefficient – Floyd‘s algorithm – Multi stage graph – Optimal Binary Search Trees – Knapsack Problem and Memory functions.
Greedy Technique – Container loading problem – Prim‘s algorithm and Kruskal’s Algorithm – 0/1 Knapsack problem, Optimal Merge pattern – Huffman Trees.
UNIT IV ITERATIVE IMPROVEMENT
The Simplex Method – The Maximum-Flow Problem – Maximum Matching in Bipartite Graphs,
Stable marriage Problem.
UNIT V COPING WITH THE LIMITATIONS OF ALGORITHM POWER
Lower – Bound Arguments – P, NP NP- Complete and NP Hard Problems. Backtracking – n-Queen
problem – Hamiltonian Circuit Problem – Subset Sum Problem. Branch and Bound – LIFO Search
and FIFO search – Assignment problem – Knapsack Problem – Travelling Salesman Problem –
Approximation Algorithms for NP-Hard Problems – Travelling Salesman problem – Knapsack
problem.
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