Article (Périodiques scientifiques)
Data-driven Mutation Analysis for Cyber-Physical Systems
VIGANO, Enrico; Cornejo, Oscar; PASTORE, Fabrizio et al.
2023In IEEE Transactions on Software Engineering
Peer reviewed vérifié par ORBi Dataset
 

Documents


Texte intégral
MAIN-DataDrivenMutationAnalysis.pdf
Postprint Auteur (3.85 MB)
Télécharger

Tous les documents dans ORBilu sont protégés par une licence d'utilisation.

Envoyer vers



Détails



Mots-clés :
Mutation Analysis; Integration testing; CPS Interoperability; Cyber-Physical Systems
Résumé :
[en] Cyber-physical systems (CPSs) typically consist of a wide set of integrated, heterogeneous components; consequently, most of their critical failures relate to the interoperability of such components. Unfortunately, most CPS test automation techniques are preliminary and industry still heavily relies on manual testing. With potentially incomplete, manually-generated test suites, it is of paramount importance to assess their quality. Though mutation analysis has demonstrated to be an effective means to assess test suite quality in some specific contexts, we lack approaches for CPSs. Indeed, existing approaches do not target interoperability problems and cannot be executed in the presence of black-box or simulated components, a typical situation with CPSs. In this paper, we introduce data-driven mutation analysis, an approach that consists in assessing test suite quality by verifying if it detects interoperability faults simulated by mutating the data exchanged by software components. To this end, we describe a data-driven mutation analysis technique (DaMAT) that automatically alters the data exchanged through data buffers. Our technique is driven by fault models in tabular form where engineers specify how to mutate data items by selecting and configuring a set of mutation operators. We have evaluated DaMAT with CPSs in the space domain; specifically, the test suites for the software systems of a microsatellite and nanosatellites launched on orbit last year. Our results show that the approach effectively detects test suite shortcomings, is not affected by equivalent and redundant mutants, and entails acceptable costs.
Centre de recherche :
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > Software Verification and Validation Lab (SVV Lab)
Disciplines :
Sciences informatiques
Auteur, co-auteur :
VIGANO, Enrico ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SVV
Cornejo, Oscar
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
Co-auteurs externes :
no
Langue du document :
Anglais
Titre :
Data-driven Mutation Analysis for Cyber-Physical Systems
Date de publication/diffusion :
01 avril 2023
Titre du périodique :
IEEE Transactions on Software Engineering
ISSN :
0098-5589
eISSN :
1939-3520
Maison d'édition :
Institute of Electrical and Electronics Engineers, New-York, Etats-Unis - New York
Peer reviewed :
Peer reviewed vérifié par ORBi
Focus Area :
Security, Reliability and Trust
Intitulé du projet de recherche :
FAQAS
Organisme subsidiant :
ASE - Agence Spatiale Européenne
Disponible sur ORBilu :
depuis le 10 octobre 2022

Statistiques


Nombre de vues
388 (dont 20 Unilu)
Nombre de téléchargements
260 (dont 16 Unilu)

citations Scopus®
 
4
citations Scopus®
sans auto-citations
3
citations OpenAlex
 
9

Bibliographie


Publications similaires



Contacter ORBilu