Towards Practical Runtime Verification and Validation of Self-Adaptive Software Systems

Tamura, Gabriel; Villegas, Norha M.; Müller, Hausi A.; Sousa, Jorge Pinho de; Becker, Basil; Karsai, Gábor; Mankovskii, Serge; Pezzè, Mauro; Schäfer, Wilhelm; Tahvildari, Ladan; Wong, Kenny

doi:10.1007/978-3-642-35813-5_5

Cited by 62 publications

(37 citation statements)

References 32 publications

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“…In the context of composition, this can be seen as developing techniques to allow evidence to be collected and collated at run time. For example, Tamura et al [45] discuss the need for validation and verification (V&V) in self-adaptive systems, and argue that run time V&V tasks should be integrated into the activities of self-adaptation. They integrate the V&V tasks into the MAPE-K loop.…”

Section: Assurance Composition Based On the Mape-k Loopmentioning

confidence: 99%

“…Another aspect of V&V discussed in [45] is viability zones, which are the set of possible systems states in which goals can be achieved that evolve with environment and context changes. This is elaborated upon in [49], which identifies adaptation zones as a way to understand the state space of self-adaptive systems, and as a framework for understanding the use of model checking in providing evidence of self-adaptive behaviour.…”

Section: Assurance Composition Based On the Mape-k Loopmentioning

confidence: 99%

“…Assuring self-adaptive systems requires run-time validation and verification (V&V) activities [45]. This is mainly because the combination of self-adaptive configurations and the environments that they encounter leads to a state explosion that makes static V&V challenging.…”

Section: Introductionmentioning

confidence: 99%

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Challenges in Composing and Decomposing Assurances for Self-Adaptive Systems

Schmerl

Andersson

Vogel

et al. 2017

Software Engineering for Self-Adaptive Systems III. Assurances

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Abstract. Self-adaptive software systems adapt to changes in the environment, in the system itself, in their requirements, or in their business objectives. Typically, these systems attempt to maintain system goals at run time and often provide assurance that they will meet their goals under dynamic and uncertain circumstances. While significant research has focused on ways to engineer selfadaptive capabilities into both new and legacy software systems, less work has been conducted on how to assure that self-adaptation maintains system goals. For traditional, especially safety-critical software systems, assurance techniques decompose assurances into sub-goals and evidence that can be provided by parts of the system. Existing approaches also exist for composing assurances, in terms of composing multiple goals and composing assurances in systems of systems. While some of these techniques may be applied to self-adaptive systems, we argue that several significant challenges remain in applying them to self-adaptive systems in this chapter. We discuss how existing assurance techniques can be applied to composing and decomposing assurances for self-adaptive systems, highlight the challenges in applying them, summarize existing research to address some of these challenges, and identify gaps and opportunities to be addressed by future research.

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Section: Assurance Composition Based On the Mape-k Loopmentioning

confidence: 99%

Section: Assurance Composition Based On the Mape-k Loopmentioning

confidence: 99%

See 1 more Smart Citation

Challenges in Composing and Decomposing Assurances for Self-Adaptive Systems

Schmerl

Andersson

Vogel

et al. 2017

Software Engineering for Self-Adaptive Systems III. Assurances

View full text Add to dashboard Cite

show abstract

“…Then, ADAM can run these userspecified rules, automatically report errors of each one of the aforementioned categories when the rule is violated at adaptation-time, and helps to identify potential defects in the rule design. Our approach is different to this one in two aspects: 1) we use a variability model to represent the adaptation rules of several configurations at the same time (i.e., as a family of configurations) and not in rules that are specified for each configuration; and 2) our approach tries to identify defects at design time to allow designers to correct them before the system is released and to avoid runtime verification, which hinders correction, and in most of cases does not scale to industrial models (Tamura et al, 2012). Further works about verification of SASs are discussed in , Villegas et al, 2011, Tamura et al, 2012.…”

Section: Verification Of Self Adaptive Systemsmentioning

confidence: 99%

Dynamic adaptation of service compositions with variability models

Alférez

Pelechano

Mazo

et al. 2014

Journal of Systems and Software

109

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Web services run in complex contexts where arising events may compromise the quality of the whole system. Thus, it is desirable to count on autonomic mechanisms to guide the self-adaptation of service compositions according to changes in the computing infrastructure. One way to achieve this goal is by implementing variability constructs at the language level. However, this approach may become tedious, difficult to manage, and error-prone. In this paper, we propose a solution based on a semantically rich variability model to support the dynamic adaptation of service compositions. When a problematic event arises in the context, this model is leveraged for decision-making. The activation and deactivation of features in the variability model result in changes in a composition model that abstracts the underlying service composition. These changes are reflected into the service composition by adding or removing fragments of Business Process Execution Language (WS-BPEL) code, which can be deployed at runtime. In order to reach optimum adaptations, the variability model and its possible configurations are verified at design time using Constraint Programming. An evaluation demonstrates several benefits of our approach, both at design time and at runtime.

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“…However, these techniques that are normally conceived as design-time activities must extend their scope to runtime and comply with the time constraints of runtime environment. We observe that the need for runtime verification and validation to detect violations and plan self-reactions demands for efficient analytical and syntactical "@runtime" techniques [2,24].…”

Section: A Research Implicationsmentioning

confidence: 99%

A Framework for Classifying and Comparing Architecture-centric Software Evolution Research

Jamshidi

Ghafari

Ahmad

et al. 2013

2013 17th European Conference on Software Maintenance and Reengineering

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Abstract-Context: Software systems are increasingly required to operate in an open world, characterized by continuous changes in the environment and in the prescribed requirements. Architecture-centric software evolution (ACSE) is considered as an approach to support software adaptation at a controllable level of abstraction in order to survive in the uncertain environment. This requires evolution in system structure and behavior that can be modeled, analyzed and evolved in a formal fashion. Existing research and practices comprise a wide spectrum of evolution-centric approaches in terms of formalisms, methods, processes and frameworks to tackle ACSE as well as empirical studies to consolidate existing research. However, there is no unified framework providing systematic insight into classification and comparison of state-of-the-art in ACSE research.Objective: We present a taxonomic scheme for a classification and comparison of existing ACSE research approaches, leading to a reflection on areas of future research. Method:We performed a systematic literature review (SLR), resulting in 4138 papers searched and 60 peer-reviewed papers considered for data collection. We populated the taxonomic scheme based on a quantitative and qualitative extraction of data items from the included studies. Results:We identified five main classification categories: (i) type of evolution, (ii) type of specification, (iii) type of architectural reasoning, (iv) runtime issues, and (v) tool support. The selected studies are compared based on their claims and supporting evidences through the scheme. Conclusion:The classification scheme provides a critical view of different aspects to be considered when addressing specific ACSE problems. Besides, the consolidation of the ACSE evidences reflects current trends and the needs for future research directions.

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Towards Practical Runtime Verification and Validation of Self-Adaptive Software Systems

Cited by 62 publications

References 32 publications

Challenges in Composing and Decomposing Assurances for Self-Adaptive Systems

Challenges in Composing and Decomposing Assurances for Self-Adaptive Systems

Dynamic adaptation of service compositions with variability models

A Framework for Classifying and Comparing Architecture-centric Software Evolution Research

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