2026-04-07T13:34:18Zhttps://ebiltegia.mondragon.edu/oai/request

oai:ebiltegia.mondragon.edu:20.500.11984/59072024-03-04T10:28:00Zcom_20.500.11984_1143col_20.500.11984_1148

00925njm 22002777a 4500 dc Ayerdi, Jon author Arrieta, Aitor author Sagardui, Goiuria author 2022 A problem when testing Cyber-Physical Systems (CPS) is the difficulty of determining whether a particular system output or behaviour is correct or not. Metamorphic testing alleviates such a problem by reasoning on the relations 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. This paper summarizes our recent publication: "Generating Metamorphic Relations for Cyber-Physical Systems with Genetic Programming: An Industrial Case Study", presented at ESEC/FSE 2021. In that publication we presented GAssertMRs, the first technique to automatically generate MRs for CPS, leveraging GP to explore the space of candidate solutions. We evaluated GAssertMRs in an industrial case study, outperforming other baselines. 978-1-4503-9268-6 https://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=169003 https://hdl.handle.net/20.500.11984/5907 cyber physical systems Metamorphic Testing Quality of Service oracle generation oracle improvement evolutionary algorithm genetic programming mutation testing Evolutionary generation of metamorphic relations for cyber-physical systems