- Computer Science Engineering (CSE)
- Design and Analysis of Algorithms
- The dynamic programming implementation o...

Q. |
## The dynamic programming implementation of the maximum sum rectangle problem uses which of the following algorithm? |

A. | hirschberg’s algorithm |

B. | needleman-wunsch algorithm |

C. | kadane’s algorithm |

D. | wagner fischer algorithm |

Answer» C. kadane’s algorithm | |

Explanation: the dynamic programming implementation of the maximum sum rectangle problem uses kadane’s algorithm. |

View all MCQs in:
Design and Analysis of Algorithms

- You are given infinite coins of N denominations v1, v2, v3,…..,vn and a sum S. The coin change problem is to find the minimum number of coins required to get the sum S. What is the time complexity of a dynamic programming implementation used to solve the coin change problem?
- What is the worst case time complexity of dynamic programming solution of set partition problem(sum=sum of set elements)?
- What will be the auxiliary space complexity of dynamic programming solution of set partition problem(sum=sum of set elements)?
- Consider the 2×3 matrix {{1,2,3},{1,2,3}}. What is the sum of elements of the maximum sum rectangle?
- Consider the 2×2 matrix {{-1,-2},{-3,-4}}. What is the sum of elements of the maximum sum rectangle?
- In the dynamic programming implementation of the assembly line scheduling problem, how many lookup tables are required?
- What is the time complexity of the above dynamic programming implementation of the assembly line scheduling problem?
- Consider the brute force implementation of the rod cutting problem in which all the possible cuts are found and the maximum value is calculated. What is the time complexity of this brute force implementation?
- In which of the following cases, the maximum sum rectangle is the 2D matrix itself?
- Recursive solution of subset sum problem is faster than dynamic problem solution in terms of time complexity.

Login to Continue

It will take less than 2 minutes

Report MCQ