Optimizing memory usage involves using the smallest possible data types, avoiding unnecessary data structures, and using pointers or references where applicable.

Memory optimization is key in competitive programming, especially in problems that involve large datasets or high memory constraints. To use memory efficiently, start by selecting the smallest possible data types; for instance, using int instead of long in languages like C++ if large values are not required. Avoid using redundant data structures and only store necessary information to minimize memory usage. For example, if you only need to track a few key values, use variables instead of arrays or lists. In languages that support pointers or references, consider using these to avoid duplicating large objects. Another useful technique is implementing sparse data structures like sparse matrices, which use memory only for non-zero entries. This is especially helpful in graph-related problems where adjacency lists can be more memory-efficient than matrices. Practicing memory-efficient coding will help you handle larger inputs and avoid memory limit exceeded errors in contests.