An Integrated Self-Testing Framework for Autonomic Computing Systems

King, Tariq M.; Ramirez, Alain E.; Cruz, Rodolfo; Clarke, Peter J.

doi:10.4304/jcp.2.9.37-49

Cited by 27 publications

(17 citation statements)

References 18 publications

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“…From this perspective, the application of run-time automatic testing techniques to enable adaptive software systems with self-testing capabilities seems to be a promising approach. An instance of this approach is the self-testing framework for autonomic computing systems proposed by King et al [31]. This framework dynamically validates change requests in requirements using regression testing and customized tests to assess the behavior of the system under the presence of added components.…”

Section: Research Challengesmentioning

confidence: 99%

Software Engineering for Self-Adaptive Systems: A Second Research Roadmap

Lemos¹,

Giese²,

Müller³

et al. 2013

Lecture Notes in Computer Science

482

347

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Abstract. The goal of this roadmap paper is to summarize the stateof-the-art and identify research challenges when developing, deploying and managing self-adaptive software systems. Instead of dealing with a wide range of topics associated with the field, we focus on four essential topics of self-adaptation: design space for self-adaptive solutions, software engineering processes for self-adaptive systems, from centralized to decentralized control, and practical run-time verification & validation for self-adaptive systems. For each topic, we present an overview, suggest future directions, and focus on selected challenges. This paper complements and extends a previous roadmap on software engineering for self-adaptive systems published in 2009 covering a different set of topics, and reflecting in part on the previous paper. This roadmap is one of the many results of the Dagstuhl Seminar 10431 on Software Engineering for Self-Adaptive Systems, which took place in October 2010.

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Section: Research Challengesmentioning

confidence: 99%

Software Engineering for Self-Adaptive Systems: A Second Research Roadmap

Lemos¹,

Giese²,

Müller³

et al. 2013

Lecture Notes in Computer Science

482

347

View full text Add to dashboard Cite

show abstract

“…To enhance reliability, self-adaptive software should employ a safe process for dynamic adaptation, and be able to validate or verify its own behavior at runtime [3], [6], [7]. Dynamic adaptation is said to be safe if it does not violate dependencies between components, or interrupt critical communications [3].…”

Section: A Autonomic and Adaptive Computingmentioning

confidence: 99%

“…Dynamic adaptation is said to be safe if it does not violate dependencies between components, or interrupt critical communications [3]. Runtime validation of adaptive software can be achieved by deploying the system with built-in tests, and mechanisms for automatically executing those tests and evaluating the results [6].…”

Section: A Autonomic and Adaptive Computingmentioning

confidence: 99%

“…More specifically, only a few researchers have addressed the need for runtime validation and verification (V&V) in self-adaptive software [6], [7]. However, since self-adaptation modifies the structure and behavior of the system, runtime V&V is necessary to ensure that errors are not introduced as a result of the adaptation process.…”

Section: Introductionmentioning

confidence: 99%

“…King et al [6] proposed the use of a runtime testing framework for validating changes in self-adaptive software. Their approach introduces an implicit self-test characteristic into autonomic and adaptive systems, which validates changes made to the software during dynamic adapation.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Towards Change Propagating Test Models in Autonomic and Adaptive Systems

Akour

Jaidev

King

2011

2011 18th IEEE International Conference and Workshops on Engineering of Computer-Based Systems

Self Cite

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Autonomic and adaptive computing systems can add, remove, and replace their own components in response to a changing environment. Self-adaptation facilitates the performance of automated maintenance and configuration tasks, but makes it possible for faults to be introduced into the software at runtime. To address this issue, researchers have developed approaches for integrating runtime testing into autonomic and adaptive software systems.An important aspect of runtime testing approaches for autonomic software is the provision of a framework for regression testing, which determines whether modifications have introduced faults into previously tested components. However, after adaptation occurs in autonomic software, a predefined test set may no longer be applicable due to changes in the program structure. Investigating techniques for dynamically updating regression tests after adaptation is therefore necessary to ensure such approaches can be applied in practice.In this paper we describe a model-driven approach that maps structural adaptations in autonomic software, to updates for its runtime test model. We provide a workflow and metamodel to support the approach, referred to as Test Information Propagation (TIP). To demonstrate TIP, we have developed a prototype that simulates a reductive change to an autonomic, service-oriented healthcare application. Conducting the simulation has provided us with much insight into this highly challenging research problem.

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Testing of adaptive and context‐aware systems: approaches and challenges

Siqueira

Ferrari

Souza

et al. 2021

Software Testing Verif & Rel

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Adaptive systems (ASs) and context-aware systems (CASs) are able to evaluate their own behaviour and to adapt it when the system fails to accomplish its goals or when better functionality or performance is possible. Ensuring the reliability of ASs and CASs is demanding because failures might have undesirable consequences. Testing ASs and CASs effectively is not trivial because of the inherent characteristics of these systems. The literature lacks a comprehensive review that provides a broad picture of the area; current reviews are outdated and incomplete. The objectives of this study are characterizing the state of the art in AS and CAS testing and discussing approaches, challenges, observed trends, and research limitations and directions. We performed a systematic literature review (SLR) and a thematic analysis of studies, reporting up-to-date, refined and extended results when compared with existing reviews. Based on 102 selected studies, we (i) characterized testing approaches by grouping techniques for ASs and CASs; (ii) updated and refined a characterization of testing challenges for ASs and CASs; and (iii) analysed and discussed research trends and implications for AS and CAS testing. There are recurring research concerns regarding AS and CAS testing. Examples are the generation of test cases and built-in tests. Moreover, we also identified recurring testing challenges such as context monitoring and runtime decisions. Moreover, there are some trends such as model-based testing and hybrid techniques and some little investigated issues like uncertainty and prediction of changes. All in all, our results may provide guidance for developers and researchers with respect to the practice and the future research on AS and CAS testing.

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An Integrated Self-Testing Framework for Autonomic Computing Systems

Cited by 27 publications

References 18 publications

Software Engineering for Self-Adaptive Systems: A Second Research Roadmap

Software Engineering for Self-Adaptive Systems: A Second Research Roadmap

Towards Change Propagating Test Models in Autonomic and Adaptive Systems

Testing of adaptive and context‐aware systems: approaches and challenges

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