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.

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

Bertolino A;
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.
2022
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Inglese
17th Symposium on Software Engineering for Adaptive and Self-Managing Systems : SEAMS 2022 : Proceedings
SEAMS 2022 - 17th Symposium on Software Engineering for Adaptive and Self-Managing Systems
58
69
978-1-4503-9305-8
https://www.computer.org/csdl/proceedings-article/seams/2022/930500a058/1ErpAzY8nx6
Sì, ma tipo non specificato
18-20/05/2022
Pittsburgh, USA
Software testing in the field
Self-adaptive testing
Knowledge gaps
3
open
Silva, S; Bertolino, A; Pelliccione, P
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/412829
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