Mutation 2020
Sat 24 Oct 2020 Porto, Portugal
co-located with ICST 2020
Sat 24 Oct 2020 15:15 - 15:30 at Arrábida - Session II

Scientists have created many cost reduction techniques for mutation testing, and most of them reduce cost with minor losses of effectiveness. However, many of these techniques are difficult to generalize, difficult to scale, or both. Published results are usually limited to a modest collection of programs. Therefore, an open question is whether the results of a given cost reduction technique on programs studied in the paper will hold true for other programs. This paper introduces a conceptual framework, named SiMut, to support the cost reduction of mutation testing based on historical data and program similarity. Given a new, untested program u, the central idea is applying to u the same cost reduction strategy applied to a group G of programs that are similar to u and have already been tested with mutation, and check for consistency of results in terms of reduced costs and quality of test sets. SiMut includes activities to compute program abstractions and similarity. Based on this information, it supports the application of mutation cost reduction techniques to both G and u. This paper presents the concepts behind SiMut, a proof-of-concept implementation of SiMut, and results from a pilot study. Finally, we discuss some issues related to the use of SiMut, focusing on the composition of a representative dataset to properly explore the potential of our framework.

Conference Day
Sat 24 Oct

Displayed time zone: Lisbon change

15:15 - 16:30
15:15
15m
Full-paper
SiMut: Exploring Program Similarity to Support the Cost Reduction of Mutation Testing
Mutation 2020
Alessandro V. PizzoletoFederal University of Sao Carlos, Fabiano FerrariFederal University of São Carlos, Lucas D. DalliloUniversity of Sao Paulo, Jeff OffuttGeorge Mason University
Link to publication DOI
15:30
15m
Full-paper
Predicting Survived and Killed Mutants
Mutation 2020
Alejandra Duque TorresInstitute of Computer Science, University of Tartu, Natia DoliashviliInstitute of Computer Science, University of Tartu, Dietmar PfahlUniversity of Tartu, Rudolf RamlerSoftware Competence Center Hagenberg
Link to publication DOI
15:45
15m
Full-paper
Fault Types of Adaptive and Context-Aware Systems and Their Relationship with Fault-based Testing Approaches
Mutation 2020
Bento Rafael SiqueiraFederal University of São Carlos, Fabiano FerrariFederal University of São Carlos, Kathiani E. SouzaFederal University of São Carlos, Daniel S. M. SantibáñezFederal University of São Carlos, Valter Vieira CamargoFederal University of São Carlos
Link to publication DOI
16:00
15m
Full-paper
MutantDistiller: Using Symbolic Execution for Automatic Detection of Equivalent Mutants and Generation of Mutant Killing Tests
Mutation 2020
Michael Baer, Norbert Oster, Michael PhilippsenFriedrich-Alexander University Erlangen-Nürnberg (FAU)
Link to publication DOI
16:15
15m
Full-paper
An Approach to Identifying Minimal and Equivalent Mutants Based on Source Code Structure
Mutation 2020
Claudinei Brito JuniorUniversidade de São Paulo, Vinicius DurelliUniversidade Federal de São João del-Rei, Rafael S. DurelliFederal University of Lavras Lavras, Simone do Rocio Senger de SouzaUniversity of São Paulo - USP, Auri VincenziFederal University of São Carlos, Marcio Eduardo DelamaroUniversidade de São Paulo
Link to publication DOI