Divide and conquer splits a problem into smaller parts, solves each, and combines results. It’s commonly used in algorithms like merge sort and binary search.

Divide and conquer is an algorithmic technique in competitive programming where a problem is broken down into smaller subproblems, each of which is solved individually before combining results to solve the original problem. This approach is fundamental in algorithms such as merge sort, quick sort, and binary search, all of which operate by recursively dividing a dataset. Divide and conquer algorithms are efficient, often achieving time complexities like O(n log n), making them ideal for large datasets. For example, merge sort divides an array into halves, sorts each half, and then merges the sorted halves. Binary search divides a sorted list in half at each step to quickly locate a target. Mastering divide and conquer enables you to tackle complex problems by approaching them as manageable subproblems, a skill essential for advanced problem-solving.