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LifnaJos/Design-Analysis-of-Algorithm-Theory

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Course : Design Analysis of Algorithm Theory (NCMPC41)

Lab Instructor Email-id Syllabus Theory Attendance
Lifna C S lifna.cs@ves.ac.in Theory & Lab Syllabus Attendance

2. Evaluation Scheme

No Rubrics Marks Document / Schedule
1 End Semester Exam 60 Marks [Old University Papers] , [Practice Problems]
2 Internal Assessment 20 Marks DAA-MT-QP-2025, DAA-MT-QP-Sol-2025
3 Continuous Assessment 20 Marks Subjected to Revision after Internal Meeting
a. Virtual Lab 10 Marks 29th Jan 2025 to 1st April 2025
b. MCQ 10 Marks
c. Programming Test on HackerRank 10 Marks DOP: 7th March 2025 to DOS25th March 2025
Total Marks 100 Marks

Note :

Continuous Assessment best out 2 of 3 will be considered

CA - 1 : HackerRank Programming Practice Set

  1. Min Max Sum
  2. Compare the Triplets
  3. Diagonal Difference
  4. Plus Minus
  5. Staircase
  6. Birthday Cake Candles
  7. Apples and Oranges
  8. Grading Students
  9. Number Line Jumps
  10. Breaking the records

CA - 2 : Virtual Lab on Sorting Techniques

  1. Selection Sort
  2. Bubble Sort
  3. Merge Sort
  4. Heap Sort
  5. Quick Sort

3. Module-wise Theory Contents

Module - 1 : Introduction to Design and Analysis of Algorithms (10 Hours) PPT

  • Performance analysis - space, and time complexity
  • Growth of function - Big-Oh, Omega & Theta notations
  • Mathematical background for algorithm analysis;
  • Analysis of selection sort, insertion sort.
  • Recurrences: The substitution method, Recursion tree method, Master method
  • Complexity Classes: Definition of P, NP, NP-Hard, NP-Complete

Online Materials:

Useful Links:

Quiz:

Module - 2: Divide and Conquer Strategy (06 Hours) PPT

  • General method,
  • Min-Max Algorithm,
  • Merge sort,
  • Quick sort,
  • Analysis of Binary search,
  • Strassen's Matrix Multiplication.

Online Resources :

Quiz :

Module - 3 : Greedy Method Approach (06 Hours) PPT

  • General Method,
  • Single source shortest path: Dijkstra Algorithm,
  • Fractional Knapsack problem,
  • Job sequencing with deadlines,
  • Minimum cost spanning trees: Kruskal and Prim’s algorithms

Online Resources :

Quiz :

Module - 4 : Dynamic Programming Approach (09 Hours) PPT

  • General Method,
  • Multistage graphs,
  • Single source shortest path: Bellman Ford Algorithm,
  • All pair shortest path: Floyd Warshall Algorithm,
  • Matrix Chain Multiplication,
  • Longest common subsequence,
  • Optimal Binary Search Trees,
  • 0/1 knapsack Problem.

Online Resources :

Quiz :

Module - 5 : Backtracking and Branch and bound (05 Hours) PPT

  • Backtracking:

    • N-queen problem,
    • Sum of subsets,
    • Graph coloring
  • Branch and Bound:

    • 15 Puzzle problem,
    • Traveling Salesperson problem.
  • Online Resources :

  • Quiz : Module - 5 Quiz

Module - 6 : String Matching Algorithms (03 Hours) PPT

  • Naïve string-matching algorithm,
  • Rabin Karp algorithm,
  • Knuth-Morris-Pratt algorithm

Online Resources:

Quiz

4. Text Books & References :

  1. T. H. Cormen, C.E. Leiserson, R. L. Rivest, and C. Stein, “Introduction to algorithms”, 2nd Edition, PHI Publication 2005.
  2. Ellis Horowitz, Sartaj Sahni, S. Rajsekaran. “Fundamentals of computer algorithms',' University Press.
  3. Sanjoy Dasgupta, Christos Papadimitriou, Umesh Vazirani, “Algorithms”, Tata McGraw Hill Edition.
  4. S. K. Basu, “Design Methods and Analysis of Algorithm”, PHI.
  5. J. Kleinberg and E. Tardos, Algorithm Design, Pearson International Edition, 2005.

5. Online Resources

  1. https://nptel.ac.in/courses/106/106/106106131/
  2. https://swayam.gov.in/nd1_noc19_cs47/preview
  3. https://www.coursera.org/specializations/algorithms
  4. https://www.mooc-list.com/tags/algorithms
  5. Stanford University

6. AI Tools

  1. Algorithmia:
  2. TensorFlow:
  3. VisuAlgo:
  4. Algorithm Visualizer:
  5. Pathfinding Visualizer:

7. Industry articles

  1. Artificial intelligence (AI) algorithms: a complete overview
  2. What Is an Algorithm?
  3. Algorithmic bias detection and mitigation: Best practices and policies to reduce consumer harms
  4. Code-Dependent: Pros and Cons of the Algorithm Age :

8. Case Studies

  1. A Case Study in Algorithm Analysis
  2. An Introduction to the Analysis of Algorithms
  3. Parallel MCMC Algorithms: Theoretical Foundations, Algorithm Design, Case Studies

Acknowledgemnts

  • This material was prepared as a part of Course - Design and Analysis of Algorithms offered by the Department of Computer Engineering, VESIT (Autonomous Institute), Affiliated to the University of Mumbai to the Second Year Students of Computer Engineering Branch during the Academic Year 2024-25

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