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Analysis and Design of AlgorithmsCSU083Analysis and Design of AlgorithmsCSU083
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Analysis and Design of Algorithms

CSU083

At a Glance

  • Credits: 4 (3+0+1)
  • Exam Split: 50% (Assignments 8, Quizzes 7, Practicals 8, Attendance 5, Midterm 12, Viva 10) / 50%
  • Note: Heavier final than the others, worth flagging loudly.
  • Lab Heavy: No
  • Units: 4
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Roadmap

Learn how to measure and optimize code performance. By the end, you'll be able to compare algorithms and choose the most efficient one for any problem.

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Units Breakdown

Unit 1: Foundations

Why it matters: Forms the mathematical basis for proving your code isn't slow.

📖 CLRS Chapters 2-4, 8, 9, 21

  • Growth of functions, Asymptotic notation
  • Linear-time sorting (counting/radix/bucket)
  • Order statistics
  • Disjoint sets
Unit 2: DP & Greedy

Why it matters: The core of modern technical interviews and optimization problems.

📖 CLRS Chapters 15, 16

  • Matrix chain multiplication
  • Strassen's algorithm
  • Longest Common Subsequence (LCS)
  • Optimal BST
  • Greedy vs DP
  • Knapsack, Huffman coding
Unit 3: Graphs

Why it matters: Powers maps, networks, and dependency resolution.

📖 CLRS Chapters 22-25

  • Representation, BFS/DFS, Topological sort, SCC
  • Kruskal & Prim (MST)
  • Dijkstra, Bellman-Ford
  • All-pairs shortest paths / Floyd-Warshall
Unit 4: String Matching

Why it matters: How search engines and text editors find things instantly.

📖 CLRS Chapter 32

  • Naive string matching
  • Rabin-Karp algorithm
  • Finite automata
  • Knuth-Morris-Pratt (KMP)