METFORD – Mutation tEsTing Framework fOR anDroid

Mutation testing may be used to guide test case generation and as a technique to assess the quality of test suites. Despite being used frequently, mutation testing is not so commonly applied in the mobile world. One critical challenge in mutation testing is dealing with its computational cost. Generating mutants, running test cases over each mutant, and analyzing the results may require significant time and resources. This research aims to contribute to reducing Android mutation testing costs. It implements mutation testing operators (traditional and Android-specific) according to mutant schemata (implementing multiple mutants into a single code file). It also describes an Android mutation testing framework developed to execute test cases and determine mutation scores. Additional mutation operators can be implemented in JavaScript and easily integrated into the framework. The overall approach is validated through case studies showing that mutant schemata have advantages over the traditional mutation strategy (one file per mutant). The results show mutant schemata overcome traditional mutation in all evaluated aspects with no additional cost: it takes 8.50% less time for mutant generation, requires 99.78% less disk space, and runs, on average, 6.45% faster than traditional mutation. Moreover, considering sustainability metrics, mutant schemata have 8,18% less carbon footprint than traditional strategy. • The METFORD framework supports mutation testing on Android apps with schemata and traditional strategies. • An experimental study with six Android apps comparing both strategies and their pros/cons. • Statistical data on Android-specific mutation operators for future framework upgrades. • Provide the tool, scripts, data, and apps in a repository for researchers to use and evolve.

Authors

Institutions

Publication Details

Journal
Journal of Systems and Software
Published
2025-01-23
DOI
https://doi.org/10.1016/j.jss.2024.112332
Citations
1
Primary Topic
Software Testing and Debugging Techniques
Type
article
Field-Weighted Citation Impact
2.31

Funders

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article

METFORD – Mutation tEsTing Framework fOR anDroid

Auri Marcelo Rizzo Vincenzi, João Bispo, Ana C. R. Paiva, Pedro Henrique Kuroishi et al.
1 citations
Journal of Systems and Software
Software Testing and Debugging Techniques
2.31
article

METFORD – Mutation tEsTing Framework fOR anDroid

Auri Marcelo Rizzo Vincenzi, João Bispo, Ana C. R. Paiva, Pedro Henrique Kuroishi, Ana R. C. da Veiga, David R. C. da Mata, Francisco B. Azevedo
article en
1 citations

Abstract

Mutation testing may be used to guide test case generation and as a technique to assess the quality of test suites. Despite being used frequently, mutation testing is not so commonly applied in the mobile world. One critical challenge in mutation testing is dealing with its computational cost. Generating mutants, running test cases over each mutant, and analyzing the results may require significant time and resources. This research aims to contribute to reducing Android mutation testing costs. It implements mutation testing operators (traditional and Android-specific) according to mutant schemata (implementing multiple mutants into a single code file). It also describes an Android mutation testing framework developed to execute test cases and determine mutation scores. Additional mutation operators can be implemented in JavaScript and easily integrated into the framework. The overall approach is validated through case studies showing that mutant schemata have advantages over the traditional mutation strategy (one file per mutant). The results show mutant schemata overcome traditional mutation in all evaluated aspects with no additional cost: it takes 8.50% less time for mutant generation, requires 99.78% less disk space, and runs, on average, 6.45% faster than traditional mutation. Moreover, considering sustainability metrics, mutant schemata have 8,18% less carbon footprint than traditional strategy. • The METFORD framework supports mutation testing on Android apps with schemata and traditional strategies. • An experimental study with six Android apps comparing both strategies and their pros/cons. • Statistical data on Android-specific mutation operators for future framework upgrades. • Provide the tool, scripts, data, and apps in a repository for researchers to use and evolve.

Journal of Systems and SoftwareVol. 222
Universidade Federal de São Carlos (BR), Universidade do Porto (PT), INESC TEC (PT)
Fundação de Amparo à Pesquisa do Estado de São Paulo, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Conselho Nacional de Desenvolvimento Científico e Tecnológico
Openalex Percentile: Top 17%
Software Testing and Debugging Techniques
2.31
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