Adaptive Software Needs Continuous Verification

TL;DR: The need and challenges for adaptively testing a DAS at run time are identified, as well as possible methods for leveraging offline testing techniques for verifying run-time behavior.

TL;DR: In this article, a branching temporal logic for expressing real-time probabilistic properties on continuous-time Markov chains (CTMCs) is introduced and approximate model checking algorithms for this logic are presented.

TL;DR: CAL is proposed, a cyber-physical system comprising a network of embedded devices for collecting and analyzing patient speech patterns over time for monitoring cognitive function beginning in the early stages of Alzheimer's disease.

TL;DR: A suite of techniques that addresses assurance for a DAS in the face of both system and environmental uncertainty at different levels of abstraction are introduced and demonstrated with applications from two different domains.

TL;DR: This chapter discusses techniques that let software react to changes by self-organizing its structure and self-adapting its behavior within today's unpredictable open-world settings.

TL;DR: A unified approach is illustrated—a method and its support tools—which facilitates reasoning about requirements satisfaction as the system evolves dynamically, and using the model’s predictive capabilities to anticipate future failures, thus enabling suitable recovery plans.

TL;DR: This paper addresses the problem of analyzing and comparing different service selection strategies and defines a framework to model the different scenarios, and reports on quantitative analyses through simulations of the modeled scenarios, highlighting advantages and limitations of each solution.