Robustness Analysis for Value-Freezing Signal Temporal Logic

In our previous work we have introduced the logic STL*, an extension of Signal Temporal Logic (STL) that allows value freezing. In this paper, we define robustness measures for STL* by adapting the robustness measures previously introduced for Metric Temporal Logic (MTL). Furthermore, we present an algorithm for STL* robustness computation, which is implemented in the tool Parasim. Application of STL* robustness analysis is demonstrated on case studies.Comment: In Proceedings HSB 2013, arXiv:1308.572

BioDiVinE: A Framework for Parallel Analysis of Biological Models

In this paper a novel tool BioDiVinEfor parallel analysis of biological models is presented. The tool allows analysis of biological models specified in terms of a set of chemical reactions. Chemical reactions are transformed into a system of multi-affine differential equations. BioDiVinE employs techniques for finite discrete abstraction of the continuous state space. At that level, parallel analysis algorithms based on model checking are provided. In the paper, the key tool features are described and their application is demonstrated by means of a case study

Reachability in Biochemical Dynamical Systems by Quantitative Discrete Approximation (extended abstract)

In this paper, a novel computational technique for finite discrete approximation of continuous dynamical systems suitable for a significant class of biochemical dynamical systems is introduced. The method is parameterized in order to affect the imposed level of approximation provided that with increasing parameter value the approximation converges to the original continuous system. By employing this approximation technique, we present algorithms solving the reachability problem for biochemical dynamical systems. The presented method and algorithms are evaluated on several exemplary biological models and on a real case study.Comment: In Proceedings CompMod 2011, arXiv:1109.104

ϵ-Semantics computations on biological systems

The assumption of being able to perform infinite precision measurements does not only lead to undecidability, but it also introduces artifacts in the mathematical models that do not correspond to observable behaviours of systems under study. When bounded spatial regions are involved, such issues can be avoided if arbitrarily small sets of points are not definable in the mathematical setting. ε-semantics were introduced in this spirit. In this paper we investigate the use of ε-semantics deeper, in the context of reachability analysis of hybrid automata. In particular, we focus on two ε-semantics and reason about their computability. We then try our approach on biological model analysis to give evidence about the effectiveness of the methodology. © 2014 Elsevier Inc