TESTING TACTICS: Software Testing Fundamentals, and White-Box Testing, White-Box Testing, Basis Path Testing, Control Structure Testing, Black-Box Testing, Object-Oriented Testing Methods, Testing for Specialized Environments, Architectures, and Applications, Testing patterns PRODUCT METRICS: Software Quality, A Framework for Product Metrics, Metrics for the Analysis Metrics for the Design Model, Metrics for Source Code, Metrics for Testing, Metrics for Maintenance. Textbooks: Roger S.Pressman, 'Software Engineering- A Practitioner's Approach', Sixth Edition, McGraw- Hill International. Reference Books: Ian Sommerville, 'Software Engineering', Sixth Edition, Pearson Education. Carlo Ghezzi, Mehdi Jazayeri, Dino Mandrioli, 'Fundamentals of Software Engineering', Second Edition, PHI. RajibMall, 'Fundamentals of Software Engineering', Second Edition, PHI. CS 325 DESIGN AND ANALYSIS OF ALGORITHMS Lectures : 4 periods/week, Tutorial: 1 Sessional Marks : 30 University Exam : 3 University Examination : 70 UNIT I – Introduction: Algorithm Design paradigms motivation, concept of algorithmic efficiency, run – time analysis of algorithms, Asymptotic Notations. Divide and Conquer: Structure of divide and conquer algorithms: examples, quick sort, Strassen Multiplication; Analysis of divide and conquer run time recurrence relations. UNIT II – Greedy Programming: Overview of the greedy paradigm examples of optimization solution, Approximate solution (Knapsack problem) Shortest-Path Algorithms Unweighted – Shortest Paths Dijkstra’s Algorithm Minimum Spanning Tree Prim’s and Kruskal’s – – – algorithms. Dynamic Programming: Overview, difference between dynamic programming and divide and conquer, Applications: Shortest path in graph, Matrix multiplication, Traveling Salesman Problem, longest Common sequence. UNIT III – Graph Searching and Traversal: Overview, Traversal methods (depth first and breadth first search), Applications of DFS connected components, Bi-connected components. – Back tracking: Overview, problem and Knapsack problem. UNIT IV – Branch and Bound: LC searching Bounding, FIFO branch and bound, LC branch and bound application: 0/1 Knapsack problem, Travelling Salesman Problem. Computational Complexity: Complexity measures, Polynomical Vs Non-polynomial time complexity; NP-hard and NP-complete classes, examples.
TESTING TACTICS: Software Testing Fundamentals, and White-Box Testing, White-Box Testing, Basis Path Testing, Control Structure Testing, Black-Box Testing, Object-Oriented Testing Methods, Testing for Specialized Environments, Architectures, and Applications, Testing patterns PRODUCT METRICS: Software Quality, A Framework for Product Metrics, Metrics for the Analysis Metrics for the Design Model, Metrics for Source Code, Metrics for Testing, Metrics for Maintenance. Textbooks: Roger S.Pressman, 'Software Engineering- A Practitioner's Approach', Sixth Edition, McGraw- Hill International. Reference Books: Ian Sommerville, 'Software Engineering', Sixth Edition, Pearson Education. Carlo Ghezzi, Mehdi Jazayeri, Dino Mandrioli, 'Fundamentals of Software Engineering', Second Edition, PHI. RajibMall, 'Fundamentals of Software Engineering', Second Edition, PHI. CS 325 DESIGN AND ANALYSIS OF ALGORITHMS Lectures : 4 periods/week, Tutorial: 1 Sessional Marks : 30 University Exam : 3 University Examination : 70 UNIT – I Introduction: Algorithm Design paradigms – motivation, concept of algorithmic efficiency, run time analysis of algorithms, Asymptotic Notations. Divide and Conquer: Structure of divide and conquer algorithms: examples, quick sort, Strassen Multiplication; Analysis of divide and conquer run time recurrence relations. UNIT – II Greedy Programming: Overview of the greedy paradigm examples of optimization solution, Approximate solution (Knapsack problem) Shortest-Path Algorithms – Unweighted Shortest Paths – Dijkstra’s Algorithm – Minimum Spanning Tree – Prim’s and Kruskal’s algorithms. Dynamic Programming: Overview, difference between dynamic programming and divide and conquer, Applications: Shortest path in graph, Matrix multiplication, Traveling Salesman Problem, longest Common sequence. UNIT – III Graph Searching and Traversal: Overview, Traversal methods (depth first and breadth first search), Applications of DFS – connected components, Bi-connected components. Back tracking: Overview, problem and Knapsack problem. UNIT – IV Branch and Bound: LC searching Bounding, FIFO branch and bound, LC branch and bound application: 0/1 Knapsack problem, Travelling Salesman Problem. Computational Complexity: Complexity measures, Polynomical Vs Non-polynomial time complexity; NP-hard and NP-complete classes, examples.
anu_b.tech_cse_Syllabus_2007_08.docx