Divide and Conquer

Computer Science and Engineering > Data Structure

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  • A Solving a problem by breaking it down into smaller subproblems
  • B Generating all possible solutions and selecting the best one
  • C Repeating the same steps over and over until a solution is found
  • D Searching for a solution by gradually eliminating possibilities
  • A Sorting a list of integers
  • B Finding the shortest path between two nodes in a graph
  • C Computing the factorial of a number
  • D Computing the greatest common divisor of two numbers
  • A O(n)
  • B O(n log n)
  • C O(n^2)
  • D O(log n)
  • A It is often slower than other approaches
  • B It requires a lot of memory
  • C It can be difficult to implement
  • D It may involve redundant computations
  • A Breaking a problem down into smaller subproblems
  • B Generating all possible solutions and selecting the best one
  • C Repeating the same steps over and over until a solution is found
  • D Searching for a solution by gradually eliminating possibilities
  • A O(n)
  • B O(n log n)
  • C O(log n)
  • D O(n^2)
  • A It only works on sorted lists
  • B It is slower than linear search for small lists
  • C It requires a lot of memory
  • D It can be difficult to implement
  • A Finding the shortest path between two nodes in a graph
  • B Computing the greatest common divisor of two numbers
  • C Finding the maximum subarray sum
  • D Computing the factorial of a number
  • A Computing the nth Fibonacci number
  • B Finding the median of two sorted arrays
  • C Sorting a linked list
  • D Finding the shortest path between two nodes in a graph
  • A It always guarantees the optimal solution
  • B It is easy to implement
  • C It is efficient for all types of problems
  • D It can be parallelized to run on multiple processors