Divide and Conquer

Solve a problem, either directly because solving that instance is easy (typically, because the instance is small) or by dividing it into two or more smaller instances. Each of these smaller instances is recursively solved, and the solutions are combined to produce a solution for the original instance.

A divide-and-conquer algorithm recursively breaks down a problem into two or more sub-problems of the same or related type, until these become simple enough to be solved directly.

This is an example of divide and conquer, which reduces the size of the problem to be more manageable.

Since an implementation by means of a sequential for-loop with p − 1 {\displaystyle p-1} iterations becomes a bottleneck, divide-and-conquer approaches are common.

Decision tree learning employs a divide and conquer strategy by conducting a greedy search to identify the optimal split points within a tree.

divides its input (a list of length n) into groups of at most five elements, computes the median of each of those groups using some subroutine, then recursively computes the true median

The algorithm works recursively by splitting an expression into its constituent subexpressions

The Floyd-Rivest algorithm is a divide-and-conquer algorithm, sharing many similarities with quickselect.

which recursively breaks down a DFT of composite size n = rm into r smaller transforms of size m

Falcon uses a divide and conquer approach similar to the Fast Fourier transform with some added noise to find the two polynomials without leaking too much information about the secret basis, hence the name.

In computer science, divide and conquer, originally a political maxim, designates an algorithm design paradigm.