When should I use backtracking?

What is backtracking and when should I use it?

Backtracking is a problem-solving technique used to find solutions by exploring all possible options. You should use it when the problem can be divided into smaller subproblems, especially in scenarios like puzzles, combinatorial problems, or constraint satisfaction problems.

Can you give me an example of a problem that uses backtracking?

Sure! A classic example is the N-Queens problem, where you need to place N queens on an N×N chessboard so that no two queens threaten each other. Backtracking helps explore different placements and backtrack when a conflict arises.

Are there any downsides to using backtracking?

Yes, backtracking can be inefficient for large problem spaces because it may explore many possibilities. However, it can be optimized with techniques like pruning to reduce the search space.

How does backtracking compare to dynamic programming?

Backtracking is more about exploring all possibilities, while dynamic programming focuses on solving problems by breaking them down into simpler subproblems and storing their solutions to avoid redundant calculations.