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Title
Towards the Isolation of Failure-Inducing Inputs in Cyber-Physical Systems: is Delta Debugging Enough?
Author
Valle Entrena, Pablo
Arrieta, Aitor
Research Group
Ingeniería del software y sistemas
Version
Postprint
Rights
© 2022 IEEE
Access
Embargoed access
URI
https://hdl.handle.net/20.500.11984/5848
Publisher’s version
https://doi.org/10.1109/SANER53432.2022.00072
Published at
IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER)  Honolulu, 15-18 March 2022. Pp. 549-553. IEEE, 2022
Publisher
IEEE
Keywords
Location awareness
Analytical models
Adaptation models
Costs ... [+]
Location awareness
Analytical models
Adaptation models
Costs
Software packages
software algorithms
Debugging [-]
Abstract
Cyber-Physical Systems (CPSs) combine digital cyber technologies with parallel physical processes. On the one hand, verification methods of such systems mostly rely on (system level) simulation-based ... [+]
Cyber-Physical Systems (CPSs) combine digital cyber technologies with parallel physical processes. On the one hand, verification methods of such systems mostly rely on (system level) simulation-based testing. This technique is expensive because complex mathematical models are used to model the physical part of CPSs. On the other hand, test cases of CPSs are usually formed by long test inputs that aim at mimicking real-world scenarios. As a result, when a failure is exhibited, it is highly important to isolate the failure-inducing inputs to provide the developers with the minimal test input. This allows reducing debugging costs by (1) reproducing the failure in the minimal time and (2) reducing the test coverage of the system, making the fault localization easier. In this paper we adapt the well-known delta debugging algorithm to isolate the failure-inducing inputs of CPSs modeled in Simulink. By means of three Simulink models, we analyzed whether Delta Debugging is effective enough to isolate failure-inducing inputs in CPSs. [-]
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Fundación BBVA
xmlui.dri2xhtml.METS-1.0.item-projectID
info:eu-repo/grantAgreement/BBVA/Becas Leonardo a Investigadores y Creadores Culturales. Tecnologías de la Información y la Comunicación 2021//ES/Depurando y Reparando Sistemas Ciber-Físico Configurables/DRAGON
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