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AutomatingTestOracleGenerationInDevOpsForIndustrialElevators.pdf (735.1Kb)
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Automating Test Oracle Generation in DevOps for Industrial Elevators
Egilea
Ibabe Arrieta, Aitor ccMondragon Unibertsitatea
OTAEGI GURRUTXAGA, MAIALEN ccMondragon Unibertsitatea
Sagardui, Goiuria ccMondragon Unibertsitatea
Egilea (beste erakunde batekoa)
Ali, Shaukat
Arratibel, Maite
Ikerketa taldea
Ingeniería del software y sistemas
Argitalpen data
2022
Argitaratzailea
IEEE
Gako-hitzak
uncertainty
Conferences
Computer bugs
Manuals ... [+]
uncertainty
Conferences
Computer bugs
Manuals
Elevators
Softwarea
Hardware [-]
Laburpena
Orona is a world-renowned elevators developer. During elevators' lives, their software continues to evolve, e.g., due to hardware obsolescence, requirements changes, vulnerabilities, and bug correctio ... [+]
Orona is a world-renowned elevators developer. During elevators' lives, their software continues to evolve, e.g., due to hardware obsolescence, requirements changes, vulnerabilities, and bug corrections. Such continuous evolution demands the continuous testing of industrial elevators with the minimum manual effort possible. To this end, we present a tool, whose core component is a domain-specific language (DSL) with which a user can specify test oracles at a higher level of abstraction and independent of a testing level. The DSL also supports specifying uncertainty-aware test oracles to test elevators under various uncertainties inherent in them. Finally, the DSL is also equipped with test oracle generation that generates test oracle code automatically at the different DevOps testing levels (i.e., Software and Hardware-in-the-Loop test levels, and in operation) to enable reuse of test oracles across these levels. We evaluated this DSL with an industrial elevators case study at Orona's site to specify and generate test oracles. The evaluation showed that the high expressiveness of the DSL permits the high-level definition of test oracles in our industrial context. Based on the industrial application, we discuss our experiences and lessons learned. [-]
URI
https://hdl.handle.net/20.500.11984/5860
Argitaratzailearen bertsioa
https://doi.org/10.1109/SANER53432.2022.00044
ISBN
978-1-6654-3786-8
Non argitaratua
2022 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER)  Marzo 16 2022
Dokumentu-mota
Kongresura ekarpena
Bertsioa
Postprinta – Accepted Manuscript
Eskubideak
© 2022 IEEE
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Sarbide bahitua (2024-07-31 arte)
Bildumak
  • Kongresuak - Ingeniaritza [242]

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