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ICSE 2021
Mon 17 May - Sat 5 June 2021

In many cases developers would like to test the program changes they introduce. To achieve this, a mutation testing formulation capable of capturing the altered program behaviours that are not adequately tested, is needed. Such a formulation of mutation testing would allow introducing relevant mutants, to the altered program behaviours, thereby allowing developers to focus, at commit time, on testing their changes. We thus introduce MuDelta an approach that identifies commit- relevant mutants; mutants that affect and are affected by the changed program behaviours. Our approach uses machine learning applied on a combined scheme of graph and vector- based representations of static code features. Our results, from 50 commits in 21 Coreutils programs, demonstrate a strong prediction ability of our approach; yielding 0.80 (ROC) and 0.50 (PR-Curve) AUC values with 0.63 and 0.32 precision and recall values. These predictions are significantly higher than random guesses, 0.20 (PR-Curve) AUC, 0.21 and 0.21 precision and recall, and subsequently lead to strong relevant tests that kill 45% more relevant mutants than randomly sampled mutants (either sampled from those residing on the changed component(s) or from the changed lines). Perhaps more importantly, our results show that our approach leads to mutants with 27% higher fault revealing ability in fault introducing commits. Taken together, our results corroborate the conclusion that commit-based mutation testing is suitable and promising for evolving software.

Conference Day
Thu 27 May

Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change

11:50 - 13:05
3.2.4. Mutation Testing: General IssuesNIER - New Ideas and Emerging Results / Journal-First Papers / Technical Track at Blended Sessions Room 4 +12h
Chair(s): Claudia AyalaUniversitat Politècnica de Catalunya, Spain, Sigrid EldhEricsson, Sweden
11:50
20m
Paper
Sentinel: A Hyper-Heuristic for the Generation of Mutant Reduction StrategiesJournal-First
Journal-First Papers
Giovani GuizzoUniversity College London, Federica SarroUniversity College London, Jens KrinkeUniversity College London, Silvia Regina VergilioFederal University of Paraná
Link to publication DOI Pre-print
12:10
15m
Short-paper
What Are We Really Testing in Mutation Testing for Machine Learning? A Critical ReflectionNIER
NIER - New Ideas and Emerging Results
Annibale PanichellaDelft University of Technology, Cynthia C. S. LiemDelft University of Technology
Pre-print Media Attached
12:25
20m
Paper
MuDelta: Delta-Oriented Mutation Testing at Commit TimeTechnical Track
Technical Track
Wei MaSnT, University of Luxembourg, Thierry Titcheu ChekamSES S.A. & University of Luxembourg (SnT), Mike PapadakisUniversity of Luxembourg, Luxembourg, Mark HarmanUniversity College London
Pre-print
12:45
20m
Paper
Does mutation testing improve testing practices?Technical Track
Technical Track
Goran PetrovićGoogle Inc, Marko IvankovićGoogle Inc, Gordon FraserUniversity of Passau, René JustUniversity of Washington
Pre-print
23:50 - 01:05
23:50
20m
Paper
Sentinel: A Hyper-Heuristic for the Generation of Mutant Reduction StrategiesJournal-First
Journal-First Papers
Giovani GuizzoUniversity College London, Federica SarroUniversity College London, Jens KrinkeUniversity College London, Silvia Regina VergilioFederal University of Paraná
Link to publication DOI Pre-print
00:10
15m
Short-paper
What Are We Really Testing in Mutation Testing for Machine Learning? A Critical ReflectionNIER
NIER - New Ideas and Emerging Results
Annibale PanichellaDelft University of Technology, Cynthia C. S. LiemDelft University of Technology
Pre-print Media Attached
00:25
20m
Paper
MuDelta: Delta-Oriented Mutation Testing at Commit TimeTechnical Track
Technical Track
Wei MaSnT, University of Luxembourg, Thierry Titcheu ChekamSES S.A. & University of Luxembourg (SnT), Mike PapadakisUniversity of Luxembourg, Luxembourg, Mark HarmanUniversity College London
Pre-print
00:45
20m
Paper
Does mutation testing improve testing practices?Technical Track
Technical Track
Goran PetrovićGoogle Inc, Marko IvankovićGoogle Inc, Gordon FraserUniversity of Passau, René JustUniversity of Washington
Pre-print