Résumé
EvoCrash is a recent search-based approach to generate a test case that reproduces reported crashes. The search is guided by a fitness function that uses a weighted sum scalarization to combine three different heuristics: (i) code coverage, (ii) crash coverage and (iii) stack trace similarity. In this study, we propose and investigate two alternatives to the weighted sum scalarization: (i) the simple sum scalarization and (ii) the multi-objectivization, which decomposes the fitness function into several optimization objectives as an attempt to increase test case diversity. We implemented the three alternative optimizations as an extension of EvoSuite, a popular search-based unit test generator, and applied them on 33 real-world crashes. Our results indicate that for complex crashes the weighted sum reduces the test case generation time, compared to the simple sum, while for simpler crashes the effect is the opposite. Similarly, for complex crashes, multi-objectivization reduces test generation time compared to optimizing with the weighted sum; we also observe one crash that can be replicated only by multi-objectivization. Through our manual analysis, we found out that when optimizing the original weighted function gets trapped in local optima, optimization for decomposed objectives improves the search for crash reproduction. Generally, while multi-objectivization is under-explored, our results are promising and encourage further investigations of the approach.
langue originale | Anglais |
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titre | Search-Based Software Engineering - 10th International Symposium, SSBSE 2018, Proceedings |
Editeur | Springer Verlag |
Pages | 325-340 |
Nombre de pages | 16 |
ISBN (imprimé) | 9783319992402 |
Les DOIs | |
Etat de la publication | Publié - 1 janv. 2018 |
Modification externe | Oui |
Evénement | 10th International Symposium on Search-Based Software Engineering, SSBSE 2018 - Montpellier, France Durée: 8 sept. 2018 → 10 sept. 2018 |
Série de publications
Nom | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 11036 LNCS |
ISSN (imprimé) | 0302-9743 |
ISSN (Electronique) | 1611-3349 |
Une conférence
Une conférence | 10th International Symposium on Search-Based Software Engineering, SSBSE 2018 |
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Pays/Territoire | France |
La ville | Montpellier |
période | 8/09/18 → 10/09/18 |
Empreinte digitale
Examiner les sujets de recherche de « Single-objective versus multi-objectivized optimization for evolutionary crash reproduction ». Ensemble, ils forment une empreinte digitale unique.Ensembles de données
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JCrashPack: A Java Crash Reproduction Benchmark
Derakhshanfar, P. (Créateur), Devroey, X. (Créateur) & Soltani, M. (Contributeur), Zenodo, 26 avr. 2020
Ensemble de données