Identifying the appropriate algorithm for a problem is a crucial skill in competitive programming that comes with experience and pattern recognition. Begin by analyzing the problem requirements and constraints, such as input size and desired efficiency, to determine suitable algorithm complexity. Recognizing patterns in the problem can also provide clues; for instance, if a problem involves subsets or combinations, backtracking or dynamic programming might be applicable. Sorting or searching problems often hint towards algorithms like binary search or quicksort. If graphs are involved, think about graph traversal techniques like DFS or BFS, or shortest-path algorithms such as Dijkstra’s. Familiarizing yourself with common problem types and associated algorithms—like sliding window for subarrays or two-pointer methods for arrays—speeds up this identification process. With practice, recognizing patterns and matching them with efficient algorithms will become a more intuitive part of your competitive programming approach.