Mathematical Programming for Anomaly Analysis of Clafer Models

Weckesser, Markus; Lochau, Malte; Ries, Michael; Schürr, Andy

doi:10.1145/3239372.3239398

Cited by 6 publications

(6 citation statements)

References 22 publications

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“…Third, Clafer provides model verification and validation [7]. By using Clafer, REACT offers the possibility for advanced static analysis as presented in Reference [89]. Thus, we can make sure that no contradictions exist in the Clafer specifications and that each possible sensor input leads to valid adaptation decisions.…”

Section: 21mentioning

confidence: 99%

“…CFMs can be translated into Boolean satisfiability (SAT) problems or mixed-integer linear programming (MILP) problems [89]. While SAT problems can be solved relatively fast with lower expressiveness, MILP problems can be applied to specifically state integer or real parameters and optimize the results using multi-objective optimization.…”

Section: Self-improvement With React-ionmentioning

confidence: 99%

“…Finally, the executing phase creates a class diagram instance of the solution space from the completed CFM. For more information on this feedback loop, the interested reader is referred to Reference [89].…”

Section: Self-improvement With React-ionmentioning

confidence: 99%

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REACT-ION: A Model-based Runtime Environment for Situation-aware Adaptations

Pfannemüller

Breitbach

Weckesser

et al. 2020

ACM Trans. Auton. Adapt. Syst.

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Trends such as the Internet of Things lead to a growing number of networked devices and to a variety of communication systems. Adding self-adaptive capabilities to these communication systems is one approach to reducing administrative effort and coping with changing execution contexts. Existing frameworks can help reducing development effort but are neither tailored toward the use in communication systems nor easily usable without knowledge in self-adaptive systems development. Accordingly, in previous work, we proposed REACT, a reusable, model-based runtime environment to complement communication systems with adaptive behavior. REACT addresses heterogeneity and distribution aspects of such systems and reduces development effort. In this article, we propose REACT-ION—an extension of REACT for situation awareness. REACT-ION offers a context management module that is able to acquire, store, disseminate, and reason on context data. The context management module is the basis for (i) proactive adaptation with REACT-ION and (ii) self-improvement of the underlying feedback loop. REACT-ION can be used to optimize adaptation decisions at runtime based on the current situation. Therefore, it can cope with uncertainty and situations that were not foreseeable at design time. We show and evaluate in two case studies how REACT-ION’s situation awareness enables proactive adaptation and self-improvement.

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Section: 21mentioning

confidence: 99%

Section: Self-improvement With React-ionmentioning

confidence: 99%

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REACT-ION: A Model-based Runtime Environment for Situation-aware Adaptations

Pfannemüller

Breitbach

Weckesser

et al. 2020

ACM Trans. Auton. Adapt. Syst.

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“…It is worth noting that other works deal with the verification of validity requirements on other types of models. For instance, Weckesser et al address the problem of checking the consistency of Clafer models [59,60], Bertram et al check the consistency of Component and Connectors view models [6,40] and Schrefl et al verify the consistency of behavior diagrams [55]. An important aspect common to all the aforementioned approaches is that the proposed verification techniques are closely correlated to the modeling language (UML/OCL, Claffer, C&C views and behavior diagrams).…”

Section: Related Workmentioning

confidence: 99%

“…Other approaches were interested in checking consistency of models expressed in other modeling languages. For instance, Weckesser et al address the problem of checking the consistency of Clafer models [59,60] and Bertram et al check the consistency of Component and Connectors view models [6,40]. As a last example, the work introduced by Schrefl and Stumpter [55] presents the particularity of checking behavioral models of the system expressed as behavior diagrams.…”

Section: Introductionmentioning

confidence: 99%

A language agnostic approach to modeling requirements

Alidra

Beugnard

Godfroy

et al. 2020

Proceedings of the 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems: Companion Proceedi

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Modeling is a complex and error prone activity which can result in ambiguous models containing omissions and inconsistencies. Many works have addressed the problem of checking models' consistency. However, most of these works express consistency requirements for a specific modeling language. On the contrary, we argue that in some contexts those requirements should be expressed independently from the modeling language of the models to be checked. We identify a set of modeling requirements in the context of embedded systems design that are expressed independently from any modeling language concrete syntax. We propose a dedicated semantic domain to support them and give a formal characterization of those requirements that is modeling language agnostic. CCS CONCEPTS • Software and its engineering → Model-driven software engineering; System modeling languages; • Computing methodologies → Model verification and validation.

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