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Mahatma Gandhi University / MG University
May 2015 Question Paper
Course: B.Tech Computer Science and Engineering
Semester: 6
Subject Code: CS010 601
Subject: Design and Analysis of Algorithms
Time Duration: 3:00 hours
Full Marks: 100
Pass Marks: 40
Part A [5*3=15 marks]
1. What are asymptotic notations ? With a figure explain any two of them used for specifying best and worst-case complexities.
2. Using recurrence, derive the complexity of merge-sort algorithm. What is the method behind the algorithm ?
3. What is multistage graph problem ?
4. What is state space tree ? Give an example.
5. Give algorithm for topological sort.
Part B [5*5=25 marks]
6. State Master's Theorem for solving recurrence. Solve: (i) T(n)=3T(n/4)+nlogn by this method.
7. Using Divide and Conquer, give an algorithm for binary search.
8. Give Prim's algorithm for obtaining a minimum spanning tree. What is the loop-invariant in the algorithm ?
9. Explain Monte-Carlo Method.
10. Explain complexity of kth element selection.
Part C [5*12=60 marks]
11. (a) Define space and time complexity. Give an example. [4 marks]
(b) Define asymptotic upper bound of T(n)=2T(n/2)+n using substitution method. [4 marks]
(c) Use recursion tree to determine a good asymptotic upper bound on the recurrence T(n)=3T(n/2)+n. [4 marks]
OR
12. Write an algorithm to sort an array of n-elements using insertion sort and derive its best and worst case runtime complexities.
13. Explain quick sort algorithm. Derive its running time. Show the various steps in quick sorting of < 13, 4, -9, 25, 1, 6, 15, 32 >.
OR
14. Give Strassen's matrix multiplication method. Compare it with the usual matrix multiplication algorithm.
15. (a) What is principle of optimality ? [3 marks]
(b) Compare 0/1 Knapsack and fractional Knapsack problem. [4 marks]
(c) Explain job sequencing with deadlines. [5 marks]
OR
16. (a) What is greedy strategy ? [3 marks]
(b) Give a greedy solution for Knapsack problem. Can greedy method used for solving 0/1 Knapsack problem ? [5 marks]
(c) Compare Dynamic programming and divide and conquer method. [4 marks]
17. State the puzzle problem. What is the best method for solving it ? Also give its complexity.
OR
18. (a) Give FIFO and LIFO control abstractions in branch and bound method. [5 marks]
(b) What is backtracking ? Give any problem that can be solved by backtracking. [7 marks]
19. (a) Write short notes on deterministic and non-deterministic algorithms. [5 marks]
(b) How is comparison tree used in searching problems ? [4 marks]
(c) What is lower bound theory ? [3 marks]
OR
20. (a) Give Las-Vegas algorithm. [6 marks]
(b) Write the steps in Rabin-Karp algorithm. [6 marks]
Mahatma Gandhi University / MG University
May 2015 Question Paper
Course: B.Tech Computer Science and Engineering
Semester: 6
Subject Code: CS010 601
Subject: Design and Analysis of Algorithms
Time Duration: 3:00 hours
Full Marks: 100
Pass Marks: 40
Part A [5*3=15 marks]
1. What are asymptotic notations ? With a figure explain any two of them used for specifying best and worst-case complexities.
2. Using recurrence, derive the complexity of merge-sort algorithm. What is the method behind the algorithm ?
3. What is multistage graph problem ?
4. What is state space tree ? Give an example.
5. Give algorithm for topological sort.
Part B [5*5=25 marks]
6. State Master's Theorem for solving recurrence. Solve: (i) T(n)=3T(n/4)+nlogn by this method.
7. Using Divide and Conquer, give an algorithm for binary search.
8. Give Prim's algorithm for obtaining a minimum spanning tree. What is the loop-invariant in the algorithm ?
9. Explain Monte-Carlo Method.
10. Explain complexity of kth element selection.
Part C [5*12=60 marks]
11. (a) Define space and time complexity. Give an example. [4 marks]
(b) Define asymptotic upper bound of T(n)=2T(n/2)+n using substitution method. [4 marks]
(c) Use recursion tree to determine a good asymptotic upper bound on the recurrence T(n)=3T(n/2)+n. [4 marks]
OR
12. Write an algorithm to sort an array of n-elements using insertion sort and derive its best and worst case runtime complexities.
13. Explain quick sort algorithm. Derive its running time. Show the various steps in quick sorting of < 13, 4, -9, 25, 1, 6, 15, 32 >.
OR
14. Give Strassen's matrix multiplication method. Compare it with the usual matrix multiplication algorithm.
15. (a) What is principle of optimality ? [3 marks]
(b) Compare 0/1 Knapsack and fractional Knapsack problem. [4 marks]
(c) Explain job sequencing with deadlines. [5 marks]
OR
16. (a) What is greedy strategy ? [3 marks]
(b) Give a greedy solution for Knapsack problem. Can greedy method used for solving 0/1 Knapsack problem ? [5 marks]
(c) Compare Dynamic programming and divide and conquer method. [4 marks]
17. State the puzzle problem. What is the best method for solving it ? Also give its complexity.
OR
18. (a) Give FIFO and LIFO control abstractions in branch and bound method. [5 marks]
(b) What is backtracking ? Give any problem that can be solved by backtracking. [7 marks]
19. (a) Write short notes on deterministic and non-deterministic algorithms. [5 marks]
(b) How is comparison tree used in searching problems ? [4 marks]
(c) What is lower bound theory ? [3 marks]
OR
20. (a) Give Las-Vegas algorithm. [6 marks]
(b) Write the steps in Rabin-Karp algorithm. [6 marks]
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