Obtaining Formal Models through Non-Monotonic Refinement

When designing a model for formal verification, we want to\ud be certain that what we proved about the model also holds for the system we modelled. This raises the question of whether our model represents the system, and what makes us confident about this. By performing so called, non-monotonic refinement in the modelling process, we make the steps and decisions explicit. This helps us to (1) increase the confidence that the model represents the system, (2) structure and organize the communication with domain experts and the problem owner, and (3) identify rational steps made while modelling. We focus on embedded control systems

The Construction of Verification Models for Embedded Systems

The usefulness of verification hinges on the quality of the verification model. Verification is useful if it increases our confidence that an artefact bahaves as expected. As modelling inherently contains non-formal elements, the qualityof models cannot be captured by purely formal means. Still, we argue that modelling is not an act of irrationalism and unpredictable geniality, but follows rational arguments, that often remain implicit. In this paper we try to identify the tacit rationalism in the model construction as performed by most people doing modelling for verification. By explicating the different phases, arguments, and design decisions in the model construction, we try to develop guidelines that help to improve the process of model construction and the quality of models

Tussen sturing en anarchie

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Hoe erg is het als studenten maar 20 uur per week studeren?

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Paradoxen in de ICT: een programma is een programma is een programma

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Modelling Embedded Systems by Non-Monotonic Refinement

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