Fuzzing explores inputs beyond a small hand-written test set. A test harness connects generated inputs to the software being examined. Some fuzzers alter existing examples and use information about which code was reached to guide further variations.
Fuzzing can uncover mistakes, but it does not prove that software is correct. Results depend on what the harness exercises and which failures the test can detect. AI can help prepare a harness, while developers still choose meaningful checks.
ELI5
Fuzzing tests how software handles lots of different inputs, including unexpected ones. It helps find cases a person might not think to write down.
For example, a text reader could be tested with empty text, unusually long words and missing punctuation. If it stops responding, that input gives developers a concrete problem to investigate.
Does fuzzing require AI?
No. Fuzzers can generate and vary inputs without AI.
Does finding no failures prove correctness?
No. Important inputs or behaviors may remain untested.
