DaMAT: A Data-driven Mutation Analysis Tool

[en] We present DaMAT, a tool that implements data- driven mutation analysis. In contrast to traditional code-driven mutation analysis tools it mutates (i.e., modifies) the data ex- changed by components instead of the source of the software under test. Such an approach helps ensure that test suites appropriately exercise components interoperability — essential for safety-critical cyber-physical systems. A user-provided fault model drives the mutation process. We have successfully evalu- ated DaMAT on software controlling a microsatellite and a set of libraries used in deployed CubeSats. A demo video of DaMAT is available at https://youtu.be/s5M52xWCj84

Research center :

Interdisciplinary Centre for Security, Reliability and Trust (SnT) > SVV - Software Verification and Validation

Disciplines :

Computer science

Author, co-author :

Vigano, Enrico ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SVV

Cornejo Olivares, Oscar Eduardo ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SVV

Pastore, Fabrizio ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SVV

Briand, Lionel ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SVV

External co-authors :

Language :

English

Title :

DaMAT: A Data-driven Mutation Analysis Tool

Publication date :

12 July 2023

Event name :

45th International Conference on Software Engineering

Event date :

from 14-05-2023 to 20-05-2023

Audience :

International

Main work title :

Companion Proceedings of the 45th International Conference on Software Engineering (ICSE ’23)

Publisher :

IEEE

Peer reviewed :

Peer reviewed

Focus Area :

Security, Reliability and Trust

Name of the research project :

RFQ/3-17554/21/NL/AS/kk/FAQAS2

Funders :

ASE - Agence Spatiale Européenne [FR]

Available on ORBilu :

since 13 March 2023

Statistics

Number of views

316 (7 by Unilu)

Number of downloads

137 (0 by Unilu)

More statistics

Scopus citations^®

Scopus citations^®
without self-citations

Bibliography

M. Papadakis, M. Kintis, J. Zhang, Y. Jia, Y. Le Traon, and M. Harman, "Mutation testing advances: an analysis and survey," in Advances in Computers. Elsevier, 2019, vol. 112, pp. 275-378.
M. Papadakis, D. Shin, S. Yoo, and D.-H. Bae, "Are mutation scores correlated with real fault detection? A large scale empirical study on the relationship between mutants and real faults," in 2018 IEEE/ACM 40th International Conference on Software Engineering (ICSE). IEEE, 2018, pp. 537-548.
O. Givehchi, K. Landsdorf, P. Simoens, and A. W. Colombo, "Interoperability for industrial cyber-physical systems: An approach for legacy systems," IEEE Transactions on Industrial Informatics, vol. 13, no. 6, pp. 3370-3378, 2017.
E. Vigaǹo, O. Cornejo, F. Pastore, and L. C. Briand, "Data-driven mutation analysis for cyber-physical systems," IEEE Transactions on Software Engineering, pp. 1-19, 2022.
O. E. Cornejo Olivares, F. Pastore, and L. Briand, "DaMAT source code." 2023. [Online]. Available: https://github.com/SNTSVV/DAMAT
E. Vigaǹo, "DaMAT tutorial." 2023. [Online]. Available: https: //github.com/SNTSVV/DAMAT Tutorial
O. E. Cornejo Olivares, F. Pastore, and L. Briand, "DaMAT replicability package." 2023. [Online]. Available: https://doi.org/10. 6084/m9.figshare.21276093
R. Natella, D. Cotroneo, and H. S. Madeira, "Assessing dependability with software fault injection: A survey," ACM Computing Surveys (CSUR), vol. 48, no. 3, p. 44, 2016.
O. Cornejo, F. Pastore, and L. C. Briand, "Mutation analysis for cyberphysical systems: Scalable solutions and results in the space domain," IEEE Transactions on Software Engineering, vol. 48, no. 10, pp. 3913- 3939, 2022.
A. Denisov and S. Pankevich, "Mull it over: mutation testing based on LLVM," in 2018 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW). IEEE, 2018, pp. 25- 31.
Joakim Brannstrom, "Dextool," https://github.com/joakim-brannstrom/ dextool/tree/master/plugin/mutate, 2021.
B. Wang, Y. Xiong, Y. Shi, L. Zhang, and D. Hao, "Faster mutation analysis via equivalence modulo states," in Proceedings of the 26th ACM SIGSOFT International Symposium on Software Testing and Analysis. ACM, 2017, pp. 295-306.
T. T. Chekam, M. Papadakis, and Y. Le Traon, "Mart: A Mutant Generation Tool for LLVM," in Proceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ser. ESEC/FSE 2019. New York, NY, USA: Association for Computing Machinery, 2019, p. 1080-1084. [Online]. Available: https://doi.org/10.1145/3338906.3341180
Y. Jia and M. Harman, "Milu: A customizable, runtime-optimized higher order mutation testing tool for the full c language," in Testing: Academic & Industrial Conference-Practice and Research Techniques (taic part 2008). IEEE, 2008, pp. 94-98.
D. L. Phan, Y. Kim, and M. Kim, "Music: Mutation analysis tool with high configurability and extensibility," in 2018 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW). IEEE, 2018, pp. 40-46.
P. Delgado-Perez, I. Medina-Bulo, F. Palomo-Lozano, A. Garcia- Dominguez, and J. J. Dominguez-Jimenez, "Assessment of class mutation operators for C++ with the mucpp mutation system," Information & Software Technology, vol. 81, pp. 169-184, 2017. [Online]. Available: https://ucase.uca.es/mucpp/index.html
M. E. Delamaro, J. C. Maldonado, and A. M. R. Vincenzi, "Proteum/im 2.0: An integrated mutation testing environment," in Mutation testing for the new century. Springer, 2001, pp. 91-101.
F. Hariri and A. Shi, "Srciror: A toolset for mutation testing of c source code and llvm intermediate representation," in Proceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering, ser. ASE '18. New York, NY, USA: Association for Computing Machinery, 2018, p. 860-863. [Online]. Available: https://doi.org/10.1145/3238147.3240482
Q. Zhu and A. Zaidman, "Mutation testing for physical computing," in 2018 IEEE International Conference on Software Quality, Reliability and Security (QRS), 2018, pp. 289-300.
"LibCSP," https://github.com/libcsp/libcsp, 2021.
LuxSpace, "ESAIL - Maritime Microsatellite," 2020. [Online]. Available: https://directory.eoportal.org/web/eoportal/satellite-missions/ e/esail