Deep Mutations have Little Impact
William B. Langdon, David Clark · 2024
Using MAGPIE (Machine Automated General Performance Improvement via Evolution of software), we measure the impact of genetic improvement (GI) on a non-deterministic deeply nested PARSEC VIPS parallel computing multi-threaded image processing benchmark written in C. More than 53% of mutants compile and generate identical results to the original program. We find about 10% Failed Disruption Propagation (FDP). Excluding internal errors and asserts, almost all changes deeper than 30 nested functions which are Executed and Infect data or change control are not Propagated to the output, i.e. these deep PIE changes have no external effect. Suggesting (where it relies on testing) automatic software engineering on deeply nested code will be hard.