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ICSE 2021
Mon 17 May - Sat 5 June 2021

Search-Based Software Engineering (SBSE) researchers who apply multi-objective search algorithms (MOSAs) often assess the quality of solutions produced by MOSAs with one or more quality indicators (QIs). However, SBSE lacks evidence providing insights on commonly used QIs, especially about agreements among them and their relations with SBSE problems and applied MOSAs. Such evidence about QIs agreements is essential to understand relationships among QIs, identify redundant QIs, and consequently devise guidelines for SBSE researchers to select appropriate QIs for their specific contexts. To this end, we conducted an extensive empirical evaluation to provide insights on commonly used QIs in the context of SBSE, by studying agreements among QIs with and without considering differences of SBSE problems and MOSAs. In addition, by defining a systematic process based on three common ways of comparing MOSAs in SBSE, we present additional observations that were automatically produced based on the results of our empirical evaluation. These observations can be used by SBSE researchers to gain a better understanding of the commonly used QIs in SBSE, in particular, regarding their agreements. Finally, based on the results, we also provide a set of guidelines for SBSE researchers to select appropriate QIs for their particular context.

Tue 25 May

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

12:05 - 13:05
1.2.2. Search-Based SE & Genetic OperationsJournal-First Papers / Technical Track at Blended Sessions Room 2 +12h
Chair(s): José Miguel Rojas University of Leicester, UK
12:05
20m
Paper
Quality Indicators in Search-Based Software Engineering: An Empirical EvaluationJournal-First
Journal-First Papers
Shaukat Ali Simula Research Laboratory, Norway, Paolo Arcaini National Institute of Informatics , Dipesh Pradhan Simula Research Laboratory, Norway, Safdar Aqeel Safdar Simula Research Laboratory, Norway, Tao Yue Simula Research Laboratory
Link to publication DOI Authorizer link Media Attached
12:25
20m
Paper
Utilizing Automatic Query Reformulations as Genetic Operations to Improve Feature Location in Software ModelsJournal-First
Journal-First Papers
Francisca Pérez SVIT Research Group, Universidad San Jorge, Tewfik Ziadi LIP6, Sorbonne Université, Carlos Cetina San Jorge University, Spain
Link to publication Pre-print Media Attached
12:45
20m
Paper
Enhancing Genetic Improvement of Software with Regression Test SelectionArtifact ReusableTechnical TrackArtifact Available
Technical Track
Giovani Guizzo University College London, Justyna Petke University College London, Federica Sarro University College London, Mark Harman University College London
Pre-print Media Attached

Wed 26 May

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

00:05 - 01:05
1.2.2. Search-Based SE & Genetic OperationsJournal-First Papers / Technical Track at Blended Sessions Room 2
00:05
20m
Paper
Quality Indicators in Search-Based Software Engineering: An Empirical EvaluationJournal-First
Journal-First Papers
Shaukat Ali Simula Research Laboratory, Norway, Paolo Arcaini National Institute of Informatics , Dipesh Pradhan Simula Research Laboratory, Norway, Safdar Aqeel Safdar Simula Research Laboratory, Norway, Tao Yue Simula Research Laboratory
Link to publication DOI Authorizer link Media Attached
00:25
20m
Paper
Utilizing Automatic Query Reformulations as Genetic Operations to Improve Feature Location in Software ModelsJournal-First
Journal-First Papers
Francisca Pérez SVIT Research Group, Universidad San Jorge, Tewfik Ziadi LIP6, Sorbonne Université, Carlos Cetina San Jorge University, Spain
Link to publication Pre-print Media Attached
00:45
20m
Paper
Enhancing Genetic Improvement of Software with Regression Test SelectionArtifact ReusableTechnical TrackArtifact Available
Technical Track
Giovani Guizzo University College London, Justyna Petke University College London, Federica Sarro University College London, Mark Harman University College London
Pre-print Media Attached