Runtime Resolution of Feature Interactions through Adaptive Requirement Weakening.
Simon Chu, Emma Shedden,
Changjian Zhang,
Rômulo Meira-Góes,
Gabriel A. Moreno,
David Garlan and
Eunsuk Kang.
In Proceedings of the 18th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, 15-16 May 2023.
Online links: Plain Text
Abstract
The feature interaction problem occurs when two or
more independently developed components interact with each
other in unanticipated ways, resulting in undesirable system
behaviors. Feature interaction problems remain a challenge for
emerging domains in cyber-physical systems (CPS), such as the
Internet of Things and autonomous drones. Existing techniques
for resolving feature interactions take a “winner-takes-all” approach, where one out of the conflicting features is selected
as the most desirable one, and the rest are disabled. However,
when multiple of the conflicting features fulfill important system
requirements, being forced to select one of them can result in
an undesirable system outcome. In this paper, we propose a new
resolution approach that allows all of the conflicting features
to continue to partially fulfill their requirements during the
resolution process. In particular, our approach leverages the
idea of adaptive requirement weakening, which involves one or
more features temporarily weakening their level of performance
in order to co-exist with the other features in a consistent
manner. Given feature requirements specified in Signal Temporal
Logic (STL), we propose an automated method and a runtime
architecture for automatically weakening the requirements to
resolve a conflict. We demonstrate our approach through case
studies on feature interactions in autonomous drones. |
Keywords: Formal Methods, Self-adaptation.
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