Advanced Data Structures and Algorithms
24CSH509 · S5 · 4 credits
Official KTU 2024 syllabus subject — study with practice, PYQs and AI tools.
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Module 01Amortized Analysisexpand
Amortized Analysis – aggregate, accounting, potential methods- Case studies. Advanced data structures: binomial heap, Fibonacci heap, disjoint sets - applications.
Module 02Network flow algorithmsexpand
Network flow algorithms: properties, Ford-Fulkerson method, maxflow-mincut theorem, Edmonds-Karp heuristics, push-relabel, relabel-to-front algorithms, maximum bipartite matching - analysis of associated algorithms - applications.
Module 03Probabilistic algorithmsexpand
Probabilistic algorithms: Numerical algorithms, integration, counting, Monte-Carlo algorithms - verifying matrix multiplication, min-cut in a network. Las Vegas algorithms, selection, quicksort, Dixon's factorization
Module 04Geometric Algorithmsexpand
Geometric Algorithms: Plane sweep technique, role of sweep- line - status and event- point-schedule, line segment intersection problem. Convex Hull: Graham’s scan algorithm, Jarvismarch algorithm. Finding closest pair of points, proof of correctness.
Module 05Number-Theoretic algorithmsexpand
Number-Theoretic algorithms: GCD algorithm, primality testing, Miller-Rabin test, integer factorization - Pollard Rho heuristic, string matching: Rabin-Karp, Knuth- Morris-Pratt algorithms. Overview of Complexity classes – P, NP, Co-NP, NP-hard, NP complete, Space complexity. Complexity classes in randomized algorithms – RP, PP, ZPP, BPP.
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