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M.B.Chandak Professor and Head of CSE mbchandak hodcs@rknec

Dive deep into algorithmic paradigms, graph algorithms, numerical algorithms, and more. Understand real-life applications and grading system. Enhance your skills in distributed and parallel systems.

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M.B.Chandak Professor and Head of CSE mbchandak hodcs@rknec

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  1. Advances in AlgorithmsFirst Semester M.Tech [CSE]CST-503 Credits: 8Weekly 4 hrs [Wednesday and Saturday] M.B.Chandak Professor and Head of CSE www.mbchandak.com hodcs@rknec.edu

  2. Curriculum • Algorithmic paradigms:Dynamic Programming, Greedy, Branch-and-Bound Asymptotic complexity, Amortized analysis. • Graph Algorithms, Shortest paths, Flow networks, NP-completeness. • Approximation algorithms, Randomized algorithms, Linear programming. • Geometric algorithms (range searching, convex hulls,segment intersections, closest pairs), • Numerical algorithms (integer, matrix and polynomial multiplication, FFT, extended Euclid’s algorithm, modular exponentiation, primarilty testing, cryptographic computations), • Internet algorithms (text pattern matching, tries, information retrieval, data compression, Web caching). • Text and String handling Algorithms: Naïve algorithm, Knuth-Morris-Pratt Algorithm, Boyer-Moore-Algorithm, Krapp-Rabin Algorithm,Approximate String Matching. • Parallel Algorithms and Architectures: Approaches to Design of Parallel Algorithm, Performance Measures of Parallel Algorithm, Parallel Sorting. • Distributed Computation Algorithm: SPMD Distributed Computation Model, Message Passing, Distribution Even-Odd Transposition Sort, Distributed Depth First Search.

  3. Course Outcome (CO) • Understand the algorithm design paradigm, methods of analysis of algorithms and classify algorithms in P and NP domains. • Understand applications of algorithms in real life problems, like searching, social network analysis, constraint handling and implementation of algorithms for distributed and parallel systems. • Understand the application of algorithms in Internet programming, search engines design and data compression. • Understand the applications of Randomized, Geometric and Numerical algorithms for solving real life problems and designing solutions.

  4. Grading Scheme • Internal Assessment: 40 marks • External Assessment: 60 marks • Internal Assessment: • Class Test T1 : 15 marks • Class Test T2 : 15 marks • Class Test T3 : 15 marks • Best of Three for 30 marks • Class Participation : 03 marks • Coding Assignment : 03 marks • Class Test/Paper : 02 marks • Class Test/Presentation : 02 marks • Assignments: • No theory writing assignment. • Students can select: one topic of interest from the course covered and deliver presentation on application of topic.* • Small project (Individual) with innovation. • Journal paper • Use of open source tool • Class Participation: • Regular Attendance • Student involvement in topic • Q/A participation in the lecture • Skill set exhibited during the lecture

  5. Text Books • Fundamentals of Computer Algorithms by Horowitz and Sahani, University Press • Introduction to Algorithm by Cormen, Rivest and Stein, PHI Publications-New Delhi, Second Edition • Design and Analysis of Computer Algorithms by: A.Ahoand John Hopcroft, Pearson Education, India. • Algorithm Design by Jon Kleinberg and Eva Tardus, Pearson Education, India.

  6. Pre-requisite • Data Structure • “C” Programming language • Design and Analysis of Algorithms (B.E course) • Logic design ability • Grading System: • Since class strength is below 30, grading system will be absolute. • Passing marks: 50 • AA: 90-100 • AB:80-90 • BB:70-80 • BC:60-70

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