Model checking: recent improvements and applications

Abstract

Model checking (Baier and Katoen in Principles of model checking, MIT Press, Cambridge, 2008 ; Clarke et al. in Model checking, MIT Press, Cambridge, 2001 ) is an automatic technique to formally verify that a given specification of a concurrent system meets given functional properties. Its use has been demonstrated many times over the years. Key characteristics that make the method so appealing are its level of automaticity, its ability to determine the absence of errors in the system (contrary to testing techniques) and the fact that it produces counter-examples when errors are detected, that clearly demonstrate not only that an error is present, but also how the error can be produced. The main drawback of model checking is its limited scalability, and for this reason, research on reducing the computational effort has received much attention over the last decades. Besides the verification of qualitative functional properties, the model checking technique can also be applied for other types of analyses, such as planning and the verification of quantitative properties. We briefly discuss several contributions in the model checking field that address both its scalability and its applicability to perform planning and quantitative analysis. In particular, we introduce six papers selected from the 23rd International SPIN Symposium on Model Checking Software (SPIN 2016).

Vessel Delineation Using U-Net: A Sparse Labeled Deep Learning Approach for Semantic Segmentation of Histological Images

“…Different formal methods, such as model checking or runtime verification, could be applied. With model checking [106][107][108], storing the deep learning code and model parameters on the blockchain could enable the verification of code execution by comparing the recorded hash or identifiers with the executed results. This would allow for easy detection of discrepancies or deviations, ensuring the correctness of the code execution.…”

A Model-Driven Approach for Reconfigurable Systems Development

“…It would also have been possible to use other software such as ATL for example. There are series of analysis tools processed this language [19]- [21]. The proposed approach can be applied to validation contexts.…”