Automated Generation of Adaptive Test Plans for Self-Adaptive Systems

Abstract

Self-adaptive systems (SAS) can reconfigure at run-time to mitigate uncertainties posed by environments for which they may not have been explicitly designed. High-assurance SAS applications must continually deliver acceptable behavior for critical services, enabling the need for run-time validation techniques. To this end, run-time testing can provide additional assurance that an SAS will continue to behave as expected while executing under unknown conditions. This paper introduces Proteus, a framework for adaptive run-time testing on an SAS. Proteus facilitates both execution and adaptation of run-time testing activities to ensure that the SAS continues to execute according to its requirements and that both test plans and test cases continually remain relevant to changing operating conditions. We demonstrate our approach by applying it to a simulated self-adaptive remote data mirroring network that must efficiently diffuse data while experiencing adverse operating conditions. Experimental results suggest that Proteus can reduce the number of executed irrelevant, false positive, and false negative test cases at run time to ensure that online testing activities remain relevant as the SAS encounters uncertainty.