In the context of algorithms, what does "divide and conquer" refer to?

In the context of algorithms, "divide and conquer" specifically refers to the strategy of breaking a problem into smaller subproblems, solving each subproblem independently, and then combining their solutions to solve the original problem. This approach is powerful because it allows complex problems to be tackled more easily by simplifying them into manageable pieces.

The process typically involves three main steps: first, divide the problem into smaller instances; second, conquer (or solve) each of those smaller instances typically using the same divide and conquer strategy; and finally, combine the solutions of the subproblems to formulate a solution to the original problem. This method is widely used in prominent algorithms, such as Merge Sort and Quick Sort, as well as in numerous other applications like finding the closest pair of points and matrix multiplication.

The other options, while related to algorithm design and analysis, do not accurately encapsulate the essence of the divide and conquer methodology. This makes the choice of breaking a problem into smaller subproblems and solving them independently the only fitting definition within the context provided.