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ISSTA 2020
Sat 18 - Wed 22 July 2020
Mon 20 Jul 2020 14:10 - 14:30 at Zoom - REPAIR AND DEBUG Chair(s): Xuan Bach D. Le

Automated generate-and-validate (G&V) program repair techniques (APR) typically rely on hard-coded rules, thus only fixing bugs following specific fix patterns. These rules require a significant amount of manual effort to discover and are hard to adapt to different programming languages. To address these challenges, we propose CoCoNuT, a new G&V technique, which uses ensemble learning on a new context-aware neural machine translation (NMT) architecture to automatically fix bugs in multiple programming languages. To better represent the context of a bug, we introduce a new context-aware NMT architecture that represents the buggy source code and its surrounding context separately. CoCoNuT also takes advantage of the randomness in hyper-parameter tuning to build multiple models that fix different bugs and combine these models using ensemble learning. Our evaluation on six popular benchmarks for four programming languages shows that CoCoNuT fixes 499 bugs, including 329 bugs that were fixed by none of the 25 techniques we compared with.

Mon 20 Jul
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13:30 - 14:30: REPAIR AND DEBUGTechnical Papers at Zoom
Chair(s): Xuan Bach D. LeThe University of Melbourne

Public Live Stream/Recording. Registered participants should join via the Zoom link distributed in Slack.

13:30 - 13:50
Technical Papers
Yiling LouPeking University, China, Ali GhanbariThe University of Texas at Dallas, Xia LiKennesaw State University, Lingming ZhangThe University of Texas at Dallas, Haotian ZhangAnt Financial, Dan HaoPeking University, Lu ZhangPeking University, China
DOI Pre-print Media Attached
13:50 - 14:10
Technical Papers
Raja Ben AbdessalemSnT Centre/University of Luxembourg, Annibale PanichellaDelft University of Technology, Shiva NejatiUniversity of Ottawa, Lionel C. BriandSnT Centre/University of Luxembourg, Thomas Stifter
DOI Pre-print
14:10 - 14:30
Technical Papers
Thibaud Lutellier, Viet Hung PhamUniversity of Waterloo, Lawrence Pang, Yitong Li, Moshi Wei, Lin TanPurdue University
DOI Media Attached