Grid Word Search: When to Use It

Start with the idea

A problem is a good match for Grid Word Search when it asks for path spelling and local grid constraints. Here the concrete task is: Return true when the word can be traced without reusing a cell. The visible input grid=ABCE,SFCS,ADEE word=ABCCED is an example, not a definition of the whole problem. Ask what operations the solution must support and what the input guarantees. Use pruning when partial choices can already be ruled out. Meet-in-the-middle instead trades two exhaustive half-enumerations for a smaller search space. The right choice follows from those guarantees, not from a familiar noun in the prompt.

The decisive invariant is: Walk matching neighbors while temporarily marking the current cell unavailable in this path. Try to say why it applies to the task without quoting the implementation. Which fact becomes known after one update, and which possible answers remain? Most patterns here explore a decision tree; meet-in-the-middle instead enumerates two halves and combines them. Define the partial choice or subset summary that the pattern retains. If that claim cannot be maintained on a legal input, the pattern is wrong or one of its preconditions is missing. A counterexample is more useful than a vague warning: change one property of the sample, trace the first two steps, and identify the exact claim that fails.

Compare costs before committing. The advertised bound is O(rows*cols*4^L) worst · O(L) depth; identify the operation responsible for it and the extra memory it needs.