Sean Sedwards

Learn More
We present PLASMA-lab, a statistical model checking (SMC) library that provides the functionality to create custom statistical model checkers based on arbitrary modelling languages. PLASMA-lab is written in Java for maximum cross-platform compatibility and has already been incorporated in various performance-critical software and embedded hardware(More)
This paper presents novel extensions and applications of the UPPAAL-SMC model checker. The extensions allow for statistical model checking of stochastic hybrid systems. We show how our race-based stochastic semantics extends to networks of hybrid systems, and indicate the integration technique applied for implementing this semantics in the UPPAAL-SMC(More)
Social, biological and economic networks grow and decline with occasional fragmentation and re-formation, often explained in terms of external perturbations. We show that these phenomena can be a direct consequence of simple imitation and internal conflicts between 'cooperators' and 'defectors'. We employ a game-theoretic model of dynamic network formation(More)
Statistical model checking offers the potential to decide and quantify dynamical properties of models with intractably large state space, opening up the possibility to verify the performance of complex real-world systems. Rare properties and long simulations pose a challenge to this approach, so here we present a fast and compact statistical model checking(More)
MOTIVATION Compartments and membranes are the basis of cell topology and more than 30% of the human genome codes for membrane proteins. While it is possible to represent compartments and membrane proteins in a nominal way with many mathematical formalisms used in systems biology, few, if any, explicitly model the topology of the membranes themselves.(More)
Transport of substances and communication between compartments are fundamental biological processes, often mediated by the presence of complementary proteins attached to the surfaces of membranes. Within compartments, substances are acted upon by local biochemical rules. Inspired by this behaviour we present a model based on Membrane Systems, with objects(More)
Markov decision processes (MDP) are useful to model concurrent process optimisation problems, but verifying them with numerical methods is often intractable. Existing approximative approaches do not scale well and are limited to memoryless schedulers. Here we present the basis of scalable verification for MDPSs, using an O(1) memory representation of(More)
Statistical model checking avoids the intractable growth of states associated with probabilistic model checking by estimating the probability of a property from simulations. Rare properties are often important, but pose a challenge for simulation-based approaches: the relative error of the estimate is unbounded. A key objective for statistical model(More)
Statistical model checking avoids the exponential growth of states associated with probabilistic model checking by estimating probabilities from multiple executions of a system and by giving results within confidence bounds. Rare properties are often important but pose a particular challenge for simulation-based approaches, hence a key objective for(More)