Optimize memory usage by using space-efficient data structures and avoiding recursion where possible.

Memory optimization is critical in competitive programming, especially when dealing with large input sizes or problems with strict memory constraints. One way to optimize memory is by using space-efficient data structures like bitmasks or sparse arrays when applicable. Another technique is to avoid deep recursion in languages like C++ or Python, which have limited stack space, and instead use iterative methods where possible. Dynamic programming problems can often be optimized by reducing the size of the memoization table or using space-saving techniques like sliding window DP. Being mindful of memory usage ensures that your solution not only runs efficiently but also fits within the problem’s constraints.