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Self-adaptive testing in the field: are we there yet?

Contributo in Atti di convegno
Data di Pubblicazione:
2022
Abstract:
Testing in the field is gaining momentum, as a means to detect those failures that escape in-house testing by continuing the testing even while a system is operating in production. Among several approaches that are proposed, this paper focuses on the important notion of self-adaptivity of testing in the field, as such techniques need to adapt in many ways their strategy to the context and the emerging behaviors of the system under test. In this work, we investigate the topic by conducting a scoping review of the literature on self-adaptive testing in the field. We rely on a taxonomy organized in some categories that include the object to adapt, the adaptation trigger, the temporal characteristics, the realization issues, the interaction concerns, the type of field-based approach, and the impact/cost. Our study sheds light on self-adaptive testing in the field by identifying related key concepts and key characteristics and extracting some knowledge gaps to better guide future research.
Tipologia CRIS:
04.01 Contributo in Atti di convegno
Keywords:
Software testing in the field; Self-adaptive testing; Knowledge gaps
Elenco autori:
Bertolino, Antonia
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/412829
Titolo del libro:
17th Symposium on Software Engineering for Adaptive and Self-Managing Systems : SEAMS 2022 : Proceedings
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URL

https://www.computer.org/csdl/proceedings-article/seams/2022/930500a058/1ErpAzY8nx6
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