TBar: Revisiting Template-based Automated Program Repair

March 20, 2019 Β· Declared Dead Β· πŸ› International Symposium on Software Testing and Analysis

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Authors Kui Liu, Anil Koyuncu, Dongsun Kim, TegawendΓ© F. BissyandΓ© arXiv ID 1903.08409 Category cs.SE: Software Engineering Citations 387 Venue International Symposium on Software Testing and Analysis Last Checked 3 months ago
Abstract
We revisit the performance of template-based APR to build comprehensive knowledge about the effectiveness of fix patterns, and to highlight the importance of complementary steps such as fault localization or donor code retrieval. To that end, we first investigate the literature to collect, summarize and label recurrently-used fix patterns. Based on the investigation, we build TBar, a straightforward APR tool that systematically attempts to apply these fix patterns to program bugs. We thoroughly evaluate TBar on the Defects4J benchmark. In particular, we assess the actual qualitative and quantitative diversity of fix patterns, as well as their effectiveness in yielding plausible or correct patches. Eventually, we find that, assuming a perfect fault localization, TBar correctly/plausibly fixes 74/101 bugs. Replicating a standard and practical pipeline of APR assessment, we demonstrate that TBar correctly fixes 43 bugs from Defects4J, an unprecedented performance in the literature (including all approaches, i.e., template-based, stochastic mutation-based or synthesis-based APR).
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