Complex recursive structures can lead to inefficient solutions. Use memoization or switch to iterative dynamic programming.

Problems with complex recursive structures often lead to inefficient solutions because of repeated calculations in overlapping subproblems. Memoization, a technique that stores the results of expensive function calls and reuses them when the same inputs occur again, can dramatically speed up these solutions. By converting a recursive solution into a top-down dynamic programming (DP) approach with memoization, you can avoid recalculating subproblems. Alternatively, consider transforming the recursive solution into an iterative bottom-up DP approach, which is usually more space-efficient and avoids the limitations of recursion depth. These techniques ensure that complex recursive problems can be solved efficiently, even with large input sizes.