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Behaviour-Driven Formal Model Development

Authors: Colin F. Snook; Thai Son Hoang; Dana Dghaym; Michael J. Butler; Tomas Fischer; Rupert Schlick; Keming Wang;

Behaviour-Driven Formal Model Development

Abstract

Formal systems modelling offers a rigorous system-level analysis resulting in a precise and reliable specification. However, some issues remain: Modellers need to understand the requirements in order to formulate the models, formal verification may focus on safety properties rather than temporal behaviour, domain experts need to validate the final models to ensure they fit the needs of stakeholders. In this paper we discuss how the principles of Behaviour-Driven Development (BDD) can be applied to formal systems modelling and validation. We propose a process where manually authored scenarios are used initially to support the requirements and help the modeller. The same scenarios are used to verify behavioural properties of the model. The model is then mutated to automatically generate scenarios that have a more complete coverage than the manual ones. These automatically generated scenarios are used to animate the model in a final acceptance stage. For this acceptance stage, it is important that a domain expert decides whether or not the behaviour is useful.

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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
11
Top 10%
Top 10%
Top 10%
Green