Ownership at Large

Ahlgren, John; Berezin, Maria Eugenia; Bojarczuk, Kinga; Dulskyte, Elena; Dvortsova, Inna; George, Johann; Gucevska, Natalija; Harman, Mark; He, Shan; Lämmel, Ralf; Meijer, Erik; Sapora, Silvia; Spahr-Summers, Justin

doi:10.1145/3387904.3389293

Cited by 5 publications

(3 citation statements)

References 29 publications

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“…We now discuss the lessons learned from this experience, and the future work for the industrial adoption of this approach. Lesson 1 -Automated generation of MRs is feasible with GAssertMRs in practice: The industrial need to identify techniques for automatically inferring metamorphic relations has been acknowledged in a recent industry-relevant study [2]. In this paper we demonstrate the advance over the state-of-the-practice in this direction by extending GAssert [39] to accommodate the needs of generating MRs in an industrial context.…”

Section: Lessons Learnedmentioning

confidence: 98%

“…In this paper we demonstrate the advance over the state-of-the-practice in this direction by extending GAssert [39] to accommodate the needs of generating MRs in an industrial context. Despite its long history, the adoption of metamorphic testing by industrial companies has started in the last few years in companies like Facebook [2], Adobe [43], or Orona [5]. Nevertheless, the definition of MRs in all these contexts has remained manual, relying on the domain knowledge of experts.…”

Section: Lessons Learnedmentioning

confidence: 99%

“…Metamorphic testing has been used in many domains, such as machine learning, web services, computer graphics, and compilers [16,32]. Recently, Facebook has adopted it for their simulation and testing infrastructure in order to tackle the test oracle problem, as well as test flakiness [2].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Generating metamorphic relations for cyber-physical systems with genetic programming: an industrial case study

Ayerdi

Terragni

Arrieta

et al. 2021

Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Softw

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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. CCS CONCEPTS• Computer systems organization → Embedded software; • Theory of computation → Assertions; • Software and its engineering → Software testing and debugging; • Computing methodologies → Genetic programming.

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Section: Lessons Learnedmentioning

confidence: 98%