Long patch validation time is a limiting factor for automated program repair (APR). Though the duality between patch validation and mutation testing is recognized, so far there exists no study of systematically adapting mutation testing techniques to general-purpose patch validation. To address this gap, we investigate existing mutation testing techniques and identify five classes of acceleration techniques that are suitable for general-purpose patch validation. Among them, mutant schemata and mutant deduplication have not been adapted to general-purpose patch validation due to the arbitrary changes that third-party APR approaches may introduce. This presents two problems for adaption: 1) the difficulty of implementing the static equivalence analysis required by the state-of-the-art mutant deduplication approach; 2) the difficulty of capturing the changes of patches to the system state at runtime. To overcome these problems, we propose two novel approaches: 1) execution scheduling, which detects the equivalence between patches online, avoiding the static equivalence analysis and its imprecision; 2) interception-based instrumentation, which intercepts the changes of patches to the system state, avoiding a full interpreter and its overhead. Based on the contributions above, we implement ExpressAPR, a general-purpose patch validator for Java that integrates all recognized classes of techniques suitable for patch validation. Our large-scale evaluation with four APR approaches shows that ExpressAPR accelerates patch validation by 137.1x over plain validation or 8.8x over the state-of-the-art approach, making patch validation no longer the time bottleneck of APR. Patch validation time for a single bug can be reduced to within a few minutes on mainstream CPUs.

Automated program repair (APR) approaches suffer from long patch validation time, which limits their practical application and receives relatively low attention. The patch validation process repeatedly executes tests to filter patches, and has been recognized as the dual of mutation analysis. We systematically investigate existing mutation testing techniques and recognize five families of acceleration techniques that are suitable for patch validation, two of which are never adapted to a general-purpose patch validator. We implement and demonstrate ExpressAPR, the first framework that combines five families of acceleration techniques for patch validation as the complete set. In our evaluation on 30 random Defects4J bugs and four APR systems, ExpressAPR accelerates patch validation for two order-of-magnitudes over plain validation or one order-of-magnitude over the state-of-the-art approach, benefiting APR researchers and users with a much shorter patch validation time. Demo video available at https://youtu.be/7AB-4VvBuuM Tool repo (source code + Docker image + evaluation dataset) available at https://github.com/ExpressAPR/ExpressAPR

Automated Program Repair (APR) helps improve the efficiency of software development and maintenance. Recent APR techniques use deep learning, particularly the encoder-decoder architecture, to generate patches. Though existing DL-based APR approaches have proposed different encoder architectures, the decoder remains to be the standard one, which generates a sequence of tokens one by one to replace the faulty statement. This decoder has multiple limitations: 1) allowing to generate syntactically incorrect programs, 2) inefficiently representing small edits, and 3) not being able to generate project-specific identifiers.