Maximum Sum Rectangle in a 2D Matrix MCQ

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• The dynamic programming implementation of the maximum sum rectangle problem uses which of the following algorithm?
  ক

  Hirschberg’s algorithm

  খ

  Needleman-Wunsch algorithm

  গ

  Kadane’s algorithm

  ঘ

  Wagner Fischer algorithm
• What is the time complexity of the brute force implementation of the maximum sum rectangle problem?
  ক

  O(n)

  খ

  O(n2)

  গ

  O(n3)

  ঘ

  O(n4)
• Consider a matrix in which all the elements are non-zero(at least one positive and at least one negative element). In this case, the sum of the elements of the maximum sum rectangle cannot be zero.
  ক

  True

  খ

  False
• Consider the following statements and select which of the following statement are true. Statement 1: The maximum sum rectangle can be 1X1 matrix containing the largest element If the matrix size is 1X1 Statement 2: The maximum sum rectangle can be 1X1 matrix containing the largest element If all the elements are zero Statement 3: The maximum sum rectangle can be 1X1 matrix containing the largest element If all the elements are negative
  ক

  Only statement 1 is correct

  খ

  Only statement 1 and Statement 2 are correct

  গ

  Only statement 1 and Statement 3 are correct

  ঘ

  Statement 1, Statement 2 and Statement 3 are correct
• In which of the following cases, the maximum sum rectangle is the 2D matrix itself?
  ক

  When all the elements are negative

  খ

  When all the elements are positive

  গ

  When some elements are positive and some negative

  ঘ

  When diagonal elements are positive and rest are negative
• Given a 2D matrix, find a submatrix that has the maximum sum. Which of the following methods can be used to solve this problem?
  ক

  Brute force

  খ

  Recursion

  গ

  Dynamic programming

  ঘ

  Brute force, Recursion, Dynamic programming