Correct and Efficient Antichain Algorithms for Refinement Checking

Laveaux, Maurice; Groote, Jan Friso; Willemse, Tim A. C.

doi:10.1007/978-3-030-21759-4_11

Cited by 4 publications

(4 citation statements)

References 22 publications

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“…Before applying this comparison check, we apply f I M to A.dm .lts as well to hide actions from used services. Since we hide the same actions on both sides and the LTSes A.dm .lts and A.mm.lts were isomorphic, surely A.im .lts SF R A.dm .lts, SFR is reflexive in nature [34]. This validates A.im .lts as interface protocol for A.dm .lts.…”

Section: Validation Of Interface Protocolmentioning

confidence: 59%

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Interface protocol inference to aid understanding legacy software components

et al. 2020

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High-tech companies are struggling today with the maintenance of legacy software. Legacy software is vital to many organizations as it contains the important business logic. To facilitate maintenance of legacy software, a comprehensive understanding of the software’s behavior is essential. In terms of component-based software engineering, it is necessary to completely understand the behavior of components in relation to their interfaces, i.e., their interface protocols, and to preserve this behavior during the maintenance activities of the components. For this purpose, we present an approach to infer the interface protocols of software components from the behavioral models of those components, learned by a blackbox technique called active (automata) learning. To validate the learned results, we applied our approach to the software components developed with model-based engineering so that equivalence can be checked between the learned models and the reference models, ensuring the behavioral relations are preserved. Experimenting with components having reference models and performing equivalence checking builds confidence that applying active learning technique to reverse engineer legacy software components, for which no reference models are available, will also yield correct results. To apply our approach in practice, we present an automated framework for conducting active learning on a large set of components and deriving their interface protocols. Using the framework, we validated our methodology by applying active learning on 202 industrial software components, out of which, interface protocols could be successfully derived for 156 components within our given time bound of 1 h for each component.

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Section: Validation Of Interface Protocolmentioning

confidence: 59%

“…The set of failures contains information about all the actions that are not allowed for each state of that LTS. For a more detailed explanation of SFR, the reader is referred to [34].…”

Section: Analytical Software Design (Asd)mentioning

confidence: 99%

Interface protocol inference to aid understanding legacy software components

et al. 2020

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“…Finally, the compliance of a component with all of its provides ports is verified by means of the ltscompare tool of mCRL2 using the Failures Refinement preorder relation known from CSP [6,13,8]. It is used to verify that the LTS of the component after hiding all internal, i.e.…”

Section: Verifying Dezyne Modelsmentioning

confidence: 99%

Dezyne: Paving the Way to Practical Formal Software Engineering

Beusekom¹,

Jonge²,

Hoogendijk³

et al. 2021

Electron. Proc. Theor. Comput. Sci.

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Designing software that controls industrial equipment is challenging, especially due to its inherent concurrent nature. Testing this kind of event driven control software is difficult and, due to the large number of possible execution scenarios only a low dynamic test coverage is achieved in practice. This in turn is undesirable due to the high cost of software failure for this type of equipment.In this paper we describe the Dezyne language and tooling; Dezyne is a programming language aimed at software engineers designing large industrial control software. We discuss its underlying two layered and compositional approach that enables reaping the benefits of Formal Methods, hereby strongly supporting guiding principles of software engineering. The core of Dezyne uses the mCRL2 language and model-checker (Jan Friso Groote et al.) to verify the correctness and completeness of all possible execution scenarios.The IDE of Dezyne is based on the Language Server Protocol allowing a smooth integration with e.g., Visual Studio Code, and Emacs, extended with several automatically generated interactive graphical views. We report on the introduction of Dezyne and its predecessor at several large high-tech equipment manufacturers resulting in a decrease of software developing time and a major decrease of reported field defects.

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“…There are a number of toolsets that support one of these two approaches. For instance, the FDR [11] toolset specialises in refinement checking, and centres around the notion of failures-divergences refinement [25,21], which facilitates a step-wise refinement software development methodology. Toolsets such as SPIN [15] and nuSMV [7] rely exclusively on model checking.…”

Section: Introductionmentioning

confidence: 99%