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Fri 13 Nov 2020 08:37 - 08:38 at Virtual room 1 - Testing 4

Finding the root cause of a bug requires a significant effort from developers. Automated fault localization techniques seek to reduce this cost by computing the suspiciousness scores (i.e., the likelihood of program entities being faulty). Existing techniques have been developed by utilizing input features of specific types for the computation of suspiciousness scores, such as program spectrum or mutation analysis results. This article presents a novel learn-to-rank fault localization technique called PRecise machINe-learning-based fault loCalization tEchnique (PRINCE). PRINCE uses genetic programming (GP) to combine multiple sets of localization input features that have been studied separately until now. For dynamic features, PRINCE encompasses both Spectrum Based Fault Localization (SBFL) and Mutation Based Fault Localization (MBFL) techniques. It also uses static features, such as dependency information and structural complexity of program entities. All such information is used by GP to train a ranking model for fault localization. The empirical evaluation on 65 real-world faults from CoREBench, 84 artificial faults from SIR, and 310 real-world faults from Defects4J shows that PRINCE outperforms the state-of-the-art SBFL, MBFL, and learn-to-rank techniques significantly. PRINCE localizes a fault after reviewing 2.4% of the executed statements on average (4.2 and 3.0 times more precise than the best of the compared SBFL and MBFL techniques, respectively). Also, PRINCE ranks 52.9% of the target faults within the top ten suspicious statements.

Fri 13 Nov
Times are displayed in time zone: (UTC) Coordinated Universal Time change

08:30 - 08:32
Talk
Journal First
Juergen GrossmannFraunhofer, Michael FeldererUniversity of Innsbruck, Johannes ViehmannFraunhofer FOKUS, Germany, Ina SchieferdeckerFraunhofer FOKUS & TU Berlin, Germany
08:33 - 08:34
Talk
Research Papers
Manuel RiggerETH Zurich, Zhendong SuETH Zurich
DOI Pre-print Media Attached
08:35 - 08:36
Talk
Research Papers
Valerio TerragniUSI Lugano, Switzerland, Gunel JahangirovaUSI Lugano, Switzerland, Paolo TonellaUSI Lugano, Switzerland, Mauro PezzeUSI Lugano, Switzerland
DOI
08:37 - 08:38
Talk
Journal First
Yunho KimKAIST, SEOKHYEON MUNKAIST, Shin YooKorea Advanced Institute of Science and Technology, Moonzoo KimKAIST and V+Lab
08:39 - 08:40
Talk
Research Papers
Alexander KampmannCISPA, Germany, Nikolas HavrikovCISPA, Germany, Ezekiel O. SoremekunCISPA, Germany, Andreas ZellerCISPA, Germany
DOI
08:41 - 09:00
Talk
Paper Presentations
Manuel RiggerETH Zurich, Valerio TerragniUSI Lugano, Switzerland, Gunel JahangirovaUSI Lugano, Switzerland, Alexander KampmannCISPA, Germany, M: Marcel BöhmeMonash University, Australia