One of the best ways to improve algorithm performance is to use algorithm design techniques, which are strategies or principles that guide you to create efficient and effective algorithms. Algorithm design techniques can be divided into two categories: problem reduction and solution construction. Problem reduction techniques, such as divide and conquer, dynamic programming, or greedy algorithms, help you simplify or transform a complex problem into smaller or easier subproblems. Solution construction techniques, such as brute force, backtracking, or heuristics, help you generate or search for a feasible or optimal solution for a problem. Algorithm design techniques help you optimize your algorithm's time and space complexity, runtime, asymptotic behavior, or empirical performance.