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ICSE 2021
Sun 16 May - Sat 5 June 2021

This program is tentative and subject to change.

Mutation testing is an effective approach to evaluate and strengthen software test suites, but its adoption is currently limited by the mutants’ execution computational cost. Several strategies have been proposed to reduce this cost (a.k.a. mutation cost reduction strategies), however none of them has proven to be effective for all scenarios since they often need an ad-hoc manual selection and configuration depending on the software under test (SUT).

In this paper, we propose a novel multi-objective evolutionary hyper-heuristic approach, dubbed Sentinel, to automate the generation of optimal cost reduction strategies for every new SUT. We evaluate Sentinel by carrying out a thorough empirical study involving 40 releases of 10 open-source real-world software systems and both baseline and state-of-the-art strategies as a benchmark. We execute a total of 4,800 experiments, and evaluate their results with both quality indicators and statistical significance tests, following the most recent best practice in the literature.

The results show that strategies generated by Sentinel outperform the baseline strategies in 95% of the cases always with large effect sizes. They also obtain statistically significantly better results than state-of-the-art strategies in 88% of the cases, with large effect sizes for 95% of them. Also, our study reveals that the mutation strategies generated by Sentinel for a given software version can be used without any loss in quality for subsequently developed versions in 95% of the cases.

These results show that Sentinel is able to automatically generate mutation strategies that reduce mutation testing cost without affecting its testing effectiveness (i.e. mutation score), thus taking off from the tester’s shoulders the burden of manually selecting and configuring strategies for each SUT.

This program is tentative and subject to change.

Thu 27 May
Times are displayed in 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
12:25
20m
Paper
MuDelta: Delta-Oriented Mutation Testing at Commit TimeTechnical Track
Technical Track
Wei MaSnT, University of Luxembourg, Thierry Titcheu ChekamUniversity 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
00:25
20m
Paper
MuDelta: Delta-Oriented Mutation Testing at Commit TimeTechnical Track
Technical Track
Wei MaSnT, University of Luxembourg, Thierry Titcheu ChekamUniversity 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

Information for Participants
Info for Blended Sessions Room 4: