Data Structure & Algorithm Takeaway: Divide and Conquer

TipWhat is divide and conquer?

Divide and conquer is an algorithm design paradigm that works by recursively breaking down a problem into two or more subproblems of the same or related type, until these become simple enough to be solved directly.

TipHow does divide and conquer work?

The divide and conquer algorithm consists of three main steps:

1. Divide: Split the problem into smaller subproblems.
2. Conquer: Solve the subproblems recursively. If they are small enough, solve them directly.
3. Combine: Merge the solutions of the subproblems into the solution for the original problem.

This is a recurvise structure and can use recursion to implement the algorithm.

WarningHow to implement divide and conquer?

The divide and conquer algorithm can be implemented using recursion:

function divide_and_conquer(problem):

    if problem is small enough:
        return base_case_solution(problem)

    // divide
    subproblems = divide(problem)

    // conquer
    for each subproblem in subproblems:
        solutions.append(divide_and_conquer(subproblem))

    // combine
    return combine(solutions)

TipPlease provide me a simple example of divide and conquer.

One classic example of a divide and conquer algorithm is the Merge Sort algorithm for sorting an array of numbers. The algorithm works as follows:

1. Divide: Split the array into two halves.
2. Conquer: Recursively sort both halves of the array.
3. Combine: Merge the two sorted halves into a single sorted array.

TipIn which scenarios can we use divide and conquer?

If a problem has the following properties, we can use divide and conquer to solve it:

• The problem can be broken down into smaller subproblems, where the solutions to the subproblems can be combined to form a solution to the original problem.
• The subproblems are independent and can be solved in parallel.