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Generating Metamorphic Relations for Cyber-Physical Systems with Genetic Progrmming_an Industrial Case Study.pdf (2.327Mb)
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Title
Generating metamorphic relations for cyber-physical systems with genetic programming: an industrial case study
Author
Ayerdi, Jon
Arrieta, Aitor
Sagardui, Goiuria
Author (from another institution)
Terragni, Valerio
Tonella, Paolo
Arratibel, Maite
Research Group
Ingeniería del software y sistemas
Other institutions
University of Auckland
Università della Svizzera italiana (USI) (Suiza)
Orona S.Coop.
Version
Postprint
Rights
© 2021 The authors
Access
Open access
URI
https://hdl.handle.net/20.500.11984/5382
Publisher’s version
https://doi.org/10.1145/3468264.3473920
Published at
Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2021).  Atenas. 25-27 agosto. Pp. 1264–1274, 2021
Publisher
ACM
Keywords
Cyber Physical Systems CPS
Metamorphic Testing
Quality of Service
oracle generation ... [+]
Cyber Physical Systems CPS
Metamorphic Testing
Quality of Service
oracle generation
oracle improvement
evolutionary algorithm
genetic programming
mutation testing [-]
Abstract
One of the major challenges in the verification of complex industrial Cyber-Physical Systems is the difficulty of determining whether a particular system output or behaviour is correct or not, the soc ... [+]
One of the major challenges in the verification of complex industrial Cyber-Physical Systems is the difficulty of determining whether a particular system output or behaviour is correct or not, the socalled test oracle problem. Metamorphic testing alleviates the oracle problem by reasoning on the relations that are expected to hold among multiple executions of the system under test, which are known as Metamorphic Relations (MRs). However, the development of effective MRs is often challenging and requires the involvement of domain experts. In this paper, we present a case study aiming at automating this process. To this end,we implemented GAssertMRs, a tool to automatically generate MRs with genetic programming. We assess the cost-effectiveness of this tool in the context of an industrial case study from the elevation domain. Our experimental results show that in most cases GAssertMRs outperforms the other baselines, including manually generated MRs developed with the help of domain experts. We then describe the lessons learned from our experiments and we outline the future work for the adoption of this technique by industrial practitioners. [-]
xmlui.dri2xhtml.METS-1.0.item-sponsorship
Comisión Europea
xmlui.dri2xhtml.METS-1.0.item-projectID
info:eu-repo/grantAgreement/EC/H2020/871319/EU/Design-Operation Continuum Methods for Testing and Deployment under Unforeseen Conditions for Cyber-Physical Systems of Systems/ADEPTNESS
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