Optimize space complexity by using in-place algorithms or removing unnecessary data structures.

Optimizing space complexity is as important as optimizing time complexity, especially in competitive programming where memory limits are strict. One way to reduce space usage is by using in-place algorithms, which modify the input data structure directly instead of using additional memory. For example, sorting algorithms like quicksort can be implemented in-place to avoid the extra space used by mergesort. Another technique is to avoid storing unnecessary data, like using iterative approaches instead of recursion to prevent stack overflows or using bit manipulation to compress boolean values into a single integer. These optimizations help keep your solution within the memory constraints imposed by the problem.