Exploring True Test Overfitting in Dynamic Automated Program Repair using Formal Methods

Abstract

Automated program repair (APR) techniques have shown a promising ability to generate patches that fix program bugs automatically. Typically such APR tools are dynamic in the sense that they find bugs by testing and they validate patches by running a program's test suite. Patches can also be validated manually. However, neither of these methods for validating patches can truly tell whether a patch is correct. Test suites are usually incomplete, and thus APR-generated patches may pass the tests but not be truly correct; in other words, the APR tools may be overfitting to the tests. The possibility of test overfitting leads to manual validation, which is costly, potentially biased, and can also..