Abstract. The analysis of complex distributed systems requires dedicated software tools. The mCRL2 language and toolset have been developed to support such analysis. We highlight changes and improvements made to the toolset in recent years. On the one hand, these affect the scope of application, which has been broadened with extended support for data structures like infinite sets and functions. On the other hand, considerable progress has been made regarding the performance of our tools for state space generation and model checking, due to improvements in symbolic reduction techniques and due to a shift towards parity gamebased solving. We also discuss the software architecture of the toolset, which was well suited to accommodate the above changes, and we address a number of case studies to illustrate the approach.
Reasoning about the correctness of parallel and distributed systems requires automated tools. By now, the mCRL2 toolset and language have been developed over a course of more than fifteen years. In this paper, we report on the progress and advancements over the past six years. Firstly, the mCRL2 language has been extended to support the modelling of probabilistic behaviour. Furthermore, the usability has been improved with the addition of refinement checking, counterexample generation and a user-friendly GUI. Finally, several performance improvements have been made in the treatment of behavioural equivalences. Besides the changes to the toolset itself, we cover recent applications of mCRL2 in software product line engineering and the use of domain specific languages (DSLs).1 The source code is also archived on https://doi.org/10.5281/zenodo.2555054.
W h e n modeling spline surfaces of complex shape, one has to deal with a n overwhelming number of control points. Modeling by direct manipulation of the control points is a tedious task. I n particular, it is very difficult to maintain a generally pleasant looking surface shape. It becomes therefore increasingly important to build tools that allow the designer to specify only a f e w geometric constraints while automatically determining the explicit representation of the surface. T h e basic concept of such a tool is simple. I n a first step one has to somehow measure the "fairness" (=quality) of a surface. Once this is achieved, a n optimization process selects the one surface with optimal fairness f r o m all surfaces satisfying the user specified geometric constraints. To measure the fairness, thin plate energy functionals are a good choice. However, for interactive use these functionals are f a r too complex. W e will present appropriate approximations to these functionals that allow a n optimization nearly in real time. T h e functionals are obtained by introducing reference surfaces thus leading t o data dependent, quadratic approximations t o the exact thin plate energy functionals. W e apply the method to interactive surface manipulations based o n energy constraints.
A constrained variational curve is a curve that minimizes some energy functional under certain interpolation constraints. Modeling curves using constrained variational principles is attractive. because the designer is not bothered with the precise representation of the curve (e.g. control points). Until now, the modeling of variational curves is mainly done by means of constraints. If such a curve of least energy is deformed locally (e.g. by moving its control points) the concept of energy minimization is lost. In this paper we introduce deform operators with built-in energy terms. We have tested our ideas in a prototype system for modeling uniform B-spline curves. Through the use of widgets, the user can interactively modify the range of influence and other properties of the operators. Experiments show that these operators offer a very intuitive way of modeling.
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