ProB: an automated analysis toolset for the B method

Leuschel, Michaël; Butler, Michael

doi:10.1007/s10009-007-0063-9

Cited by 311 publications

(168 citation statements)

References 42 publications

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“…balance − { a2 → 300} = { a1 → 100, a2 → 300, a3 → 800, a4 → 50 } A very useful validation technique for Event-B models is to use an animation tool such as ProB [4] or AnimB 2 . With these tools, the carrier sets are instantiated with some illustrative values, e.g., the carrier set USER is instantiated with the values u1, u2, u3, and the model can be executed with these values.…”

Section: Function Overridementioning

confidence: 99%

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Reasoned Modelling with Event-B

Butler

2017

Engineering Trustworthy Software Systems

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Abstract. This paper provides an overview of how the Event-B language and verification method can be used to model and reason about system behaviour. Formal modelling and reasoning help to increase understanding and reduce defects in requirements specification. Sets and relations play a key role in modelling as do operators on these structures. Precise definitions and rules are provided in order to help the reader gain a strong understanding of the mathematical operators for sets and relations. While the emphasis is on mathematical reasoning, particularly through invariant proofs, the paper also covers less formal reasoning such as identification of problem entities supported by class diagrams and validation of formal models against informal requirements. The use of tools for animation, model checking and proof is also outlined.

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Section: Function Overridementioning

confidence: 99%

“…The Atelier B tool 5 supports the B Method. For details of the ProB tool see [4] and the ProB website 6 . ProB is available as a plug-in for Rodin as is the AnimB tool 7 .…”

Section: Further Readingmentioning

confidence: 99%

Reasoned Modelling with Event-B

Butler

2017

Engineering Trustworthy Software Systems

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“…The advantage of Murray's interpretation of SEF and WEF is that they are refinement-closed in RT . As temporal properties constrained by SEF or WEF cannot in general be expressed as refinement checks for FDR [4], we propose the use of ProB [14], which enables LTL model checking of CSP processes using the following grammar [5].…”

Section: Model Checking Under Fairness Constraints In Probmentioning

confidence: 99%

Model Checking under Fairness in ProB and Its Application to Fair Exchange Protocols

Williams

Ruiter

Fokkink

2012

Theoretical Aspects of Computing – ICTAC 2012

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Abstract. Motivated by Murray's work on the limits of refinement testing for CSP, we propose the use of ProB to check liveness properties under assumptions of strong and weak event fairness, whose refinement-closures cannot generally be expressed as refinement checks for FDR. Such properties are necessary for the analysis of fair exchange protocols in CSP, which assume at least some messages are sent over a resilient channel. As the properties we check are refinement-closed, we retain CSP's theory of refinement, enabling subsequent step-wise refinement of the CSP model. Moreover, we improve upon existing CSP models of fair exchange protocols by proposing a revised intruder model inspired by the one of Cederquist and Dashti. Our intruder model is stronger as we use a weaker fairness constraint.

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“…Both languages are rooted in set-theory and support different higher order data types like relations, functions and sequences. ProB [19,20] is a model checker for both languages featuring explicit state model checking as well as different constraint based techniques [13,18] for the analysis of specifications.…”

Section: Introductionmentioning

confidence: 99%

“…Originally, the ProB kernel has been tailored towards satisfiable formulas, acting primarily as a model finder [19,20]. Recent additions to ProB have extended the kernel in a different direction.…”

Section: Introductionmentioning

confidence: 99%

SMT Solvers for Validation of B and Event-B Models

Krings

Leuschel

2016

Lecture Notes in Computer Science

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Abstract. We present an integration of the constraint solving kernel of the ProB model checker with the SMT solver Z3. We apply the combined solver to B and Event-B predicates, featuring higher-order datatypes and constructs like set comprehensions. To do so we rely on the finite set logic of Z3 and provide a new translation from B to Z3, better suited for constraint solving. Predicates can then be solved by the two solvers working hand in hand: constraints are set up in both solvers simultaneously and (intermediate) results are transferred. We thus combine a constraint logic programming based solver with a DPLL(T) based solver into a single procedure. The improved constraint solver finds application in many validation tasks, from animation of implicit specifications, to test case generation, bounded and symbolic model checking on to disproving of proof obligations. We conclude with an empirical evaluation of our approach focusing on two dimensions: comparing low and high-level encodings of B as well as comparing pure ProB to ProB combined with Z3.

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ProB: an automated analysis toolset for the B method

Cited by 311 publications

References 42 publications

Reasoned Modelling with Event-B

Reasoned Modelling with Event-B

Model Checking under Fairness in ProB and Its Application to Fair Exchange Protocols

SMT Solvers for Validation of B and Event-B Models

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