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Teaching                                                                                                              Calendar

Currently Teaching

• MCA 202: Discrete Mathematics

Courses Taught During July 2012 - November 2012

• MCA 301: Design and Analysis of Algorithms

MCA 301: Design and Analysis of Algorithms Syllabus Introduction: RAM model, O(log n) bit model. Review of data structures: Balanced trees, Mergeable sets. Algorithm Design Techniques: Iterative techniques, Divide and conquer, dynamic programming, greedy algorithms. Searching and Sorting Techniques: Review of elementary sorting techniques-selection sort, bubble sort, insertion sort; more sorting techniques-quick sort, heap sort, merge sort, shell sort; external sorting. Lower bounding techniques: Decision Trees, Adversaries. String Processing: KMP, Boyre-Moore, Robin Karp algorithms. Introduction to randomized algorithms: Random numbers, randomized Qsort, randomly Built BST. Number Theoretic Algorithms: GCD, Addition and Multiplication of two large numbers, polynomial arithmetic, Fast-Fourier Transforms. Graphs: Analysis of Graph algorithms Depth-First Search and its applications, minimum Spanning Trees and Shortest Paths. Introduction to Complexity Theory: Class P, NP, NP-Hard, NP Completeness. Introduction to Approximation Algorithms. References T.H. Cormen, C.E. Leiserson, R.L. Rivest and C. Stein, Indtroduction to Algoritms, Prentice-Hall of India, 2006. J. Kleinberg and E.Tardos, Algorithms Design, Pearson Education, 2006. S.Baase, Computer algorithms: Introduction to Design and Analysis, Addison Wesley, 1999. A.V. Levitin, Introduction to the Design and Analysis of algorithms, Pearson Education, 2006. Lecture Notes of 2012 Introduction Lecture 1 - Mathematical Induction: Review Growth Functions Lecture 2 - Recurrence Relation Lecture 3 - Correctness of Algorithm Lecture 4 - Comparision Sorting Lecture 5 - Lbound Linear Sorting Lecture 6 - Selection Adversary Lecture 7 - String Matching Lecture 8 - Greedy Algorithms Lecture 9 - Dynamic Programming Lecture 10 - Expected Running Times and Random Algorithms Lecture 11 - Analysis of Graph Algorithms Some Lecture Notes of Previous Years Introduction Lecture 1 - Mathematical Induction: Review Growth Functions Lecture 2 - Solving Recurrences The Master Theorem Lecture 3 - Proving Correctness of Algorithms Lecture 4 - Comparison Sorting Lecture 5 - Lower Bounds Linear-Time Sorting Algorithms Lecture 6 - Selection Adversary Lecture 7 - Analysis Red-Black Trees Lecture 8 - NP - Completeness Previous Years Minors Minor I'12 Minor II'12 Minor I'07 Minor II'07 Minor I'06 Minor II'06 Minor I'05 Minor II'05

• MCS 312: Special Topics in Theoretical Computer Science

Subjects Taught Previously

Undergraduate Level

• 1989 - 2002: Systems Analysis and Design, Computer System Architecture, Programming languages from COBOL, Pascal to C, Discrete Structures, Data Structures, Algorithms, Theory of Computation/ Automata Theory, Statistical Techniques

Postgraduate Level

• 2002 - till date: Systems Programming, Data Communication and Computer Networks, Design and Analysis of Algorithms, Algorithms in Bioinformatics, NP Completeness and Approximation Algorithms.

• MCS 101: Design and Analysis of Algorithms

• MCA 204: Data Communication and Computer Networks