Aho–Corasick: When to Use It

Start with the idea

A problem is a good match for Aho–Corasick when it asks for many-pattern search, filters, signature scanning. Here the concrete task is: Return matched pattern count including overlaps. The visible input text=ahishers patterns=[he,she,his,hers] is an example, not a definition of the whole problem. Ask what operations the solution must support and what the input guarantees. Look for repeated prefix queries or pattern matching before choosing a trie or preprocessing; a one-off short search may not need either. The right choice follows from those guarantees, not from a familiar noun in the prompt.

The decisive invariant is: Add failure links to a trie so one scan reports all pattern suffixes ending at each position. 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? String algorithms compare symbols or prefixes, but a Rust String is UTF-8 bytes. State whether the task means bytes, scalar values, or grapheme clusters. 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(text + matches + total patterns) time; identify the operation responsible for it and the extra memory it needs.