Divide and Conquer
An algorithm design paradigm that breaks a problem into smaller sub-problems, solves them independently, and combines their solutions to solve the original problem.
Definition
A strategy that divides a problem into smaller sub-problems, solves each sub-problem independently, and combines their solutions to solve the original problem.
Steps
- Divide: Split the problem into smaller sub-problems.
- Conquer: Solve each sub-problem recursively.
- Combine: Merge the solutions of the sub-problems.
Examples
- Merge Sort: Divides the array into halves, sorts them, and merges.
- Quick Sort: Divides the array using a pivot and recursively sorts partitions.
- Binary Search: Divides the search space in half at each step.
Advantages
- Simplifies complex problems.
- Efficient for large datasets.