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BEARS: An Extensible Java Bug Benchmark for Automatic Program Repair Studies
KTH, School of Electrical Engineering and Computer Science (EECS), Theoretical Computer Science, TCS.ORCID iD: 0000-0003-3505-3383
2019 (English)In: SANER 2019 - Proceedings of the 2019 IEEE 26th International Conference on Software Analysis, Evolution, and Reengineering, Institute of Electrical and Electronics Engineers (IEEE), 2019, p. 468-478, article id 8667991Conference paper, Published paper (Refereed)
Abstract [en]

Benchmarks of bugs are essential to empirically evaluate automatic program repair tools. In this paper, we present BEARS, a project for collecting and storing bugs into an extensible bug benchmark for automatic repair studies in Java. The collection of bugs relies on commit building state from Continuous Integration (CI) to find potential pairs of buggy and patched program versions from open-source projects hosted on GitHub. Each pair of program versions passes through a pipeline where an attempt of reproducing a bug and its patch is performed. The core step of the reproduction pipeline is the execution of the test suite of the program on both program versions. If a test failure is found in the buggy program version candidate and no test failure is found in its patched program version candidate, a bug and its patch were successfully reproduced. The uniqueness of Bears is the usage of CI (builds) to identify buggy and patched program version candidates, which has been widely adopted in the last years in open-source projects. This approach allows us to collect bugs from a diversity of projects beyond mature projects that use bug tracking systems. Moreover, BEARS was designed to be publicly available and to be easily extensible by the research community through automatic creation of branches with bugs in a given GitHub repository, which can be used for pull requests in the BEARS repository. We present in this paper the approach employed by BEARS, and we deliver the version 1.0 of BEARS, which contains 251 reproducible bugs collected from 72 projects that use the Travis CI and Maven build environment.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2019. p. 468-478, article id 8667991
Keywords [en]
Java programming language, Open source software, Pipelines, Reengineering, Repair, Software testing, Automatic creations, Automatic programs, Bug tracking system, Continuous integrations, Open source projects, Repair tools, Research communities, Test failure, Program debugging
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:kth:diva-252215DOI: 10.1109/SANER.2019.8667991ISI: 000469754100045Scopus ID: 2-s2.0-85064151415ISBN: 9781728105918 (print)OAI: oai:DiVA.org:kth-252215DiVA, id: diva2:1322959
Conference
26th IEEE International Conference on Software Analysis, Evolution, and Reengineering, SANER 2019, 24 February 2019 through 27 February 2019
Funder
Wallenberg AI, Autonomous Systems and Software Program (WASP)Swedish Foundation for Strategic Research , Trustfull
Note

QC 20190611

Available from: 2019-06-11 Created: 2019-06-11 Last updated: 2019-09-09Bibliographically approved

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Monperrus, Martin

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