Design And Analysis Of Algorithms Syllabus
Periods/week : 3 Periods & 1 Tut /week. Ses. : 30 Exam : 70 Examination (Practical): 3hrs. Credits: 4
Introduction – Fundamentals of algorithmic problem solving – important problem types –
fundamental data structures.
Fundamentals of analysis of algorithms and efficiency – Analysis framework – Asymptotic Notations and Basic Efficiency classes – Mathematical Analysis of Non-recursive Algorithms – Mathematical Analysis of recursive Algorithms – Empirical Analysis of Algorithms – Algorithm Visualization
Brute Force – Selection Sort and Bubble sort – Sequential Search and Brute – Force String
Matching – Closest Pair and Convex-Hull Problems by Brute Force – Exhaustive Search
Divide-and-Conquer – Mergesort – Quicksort – Binary Search – Binary Tree Traversals and Related Properties – Multiplication of large integers and Strassen’s Matrix Multiplication – Closest- Pair Convex-Hull Problems by Divide- and – Conquer
Decrease – and – Conquer – Insertion Sort – Depth-First Search and Breadth-First Search- Topological Sorting – Algorithms for Generating Combinatorial Objects – Decrease-by-a- Constant-Factor Algorithms – Variable-Size-Decrease Algorithms
Transform-and-Conquer – Presorting – Gaussian Elimination – Balanced Search Trees – Heaps and Heapsort – Horner’s Rule and Binary Exponentiation – Problem Reduction
Space and Time Tradeoffs – Sorting by Counting – Input Enhancement in string Matching – Hashing – B-Trees
Dynamic Programming – Computing a Binomial Coefficient – Warshall’s and Floyd’s Algorithm
– Optimal Binary Search Trees – The Knapsack Problem and Memory Functions.
Greedy Technique – Prim’s Algorithm – Kruskal’s Algorithm – Dijkstra’s Algorithm –
Huffman Trees Limitations of Algorithm Power – Lower-Bound Arguments – Decision Trees – P, NP and NP – complete problems – Challenges of Numerical Algorithms
Coping with the Limitations of Algorithms Power – Backtracking – Branch-and-Bound – Approximation Algorithms for NP-hard Problems – Algorithms for solving Nonlinear Equations.
Introduction to Design & Analysis of Algorithms by Anany Levitin, Pearson Education, New
1. Introduction to Algorithms by Thomas H. Corman, Charles E. Leiserson, Ronald R. Rivest & Clifford Stein, Prentice Hall of India, New Delhi, New Delhi
2. The Design and Analysis of computer Algorithms, Aho, Hopcroft & Ullman, Pearson
Education, New Delhi, 2003
3. Fundamentals of algorithmics, Gilles Brassard & Paul Bratley, Prentice Hall of India, New
Delhihttp://www.stepinau.com/2013/09/22/design-and-analysis-of-algorithms-syllabus/CSE 3.2 SyllabusIT 3.2 SyllabusCSE,CSE Syllabus,Design And Analysis Of Algorithms Syllabus,IT,IT Syllabus