Divide and Conquer is a fundamental algorithm design technique that breaks a problem into smaller subproblems, solves each independently, and then combines their results to form the final solution.
Divide → Split array into two halves
Conquer → Sort both halves recursively
Combine → Merge sorted halvesTime Complexity: O(n log n)
Divide → Partition array around a pivot
Conquer → Recursively sort subarrays
Combine → No explicit merge stepTime Complexity: O(n log n) (average), O(n²) (worst)
Repeatedly divide the search space in half until the element is found.
Time Complexity: O(log n)
Divides matrices into submatrices to multiply faster than the standard O(n³) method.
Divide and Conquer simplifies problem-solving by applying recursion logically. It forms the basis for many efficient algorithms like Merge Sort, Quick Sort, and Binary Search.
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