Petri nets for systems and synthetic biology

We give a description of a Petri net-based framework for modelling and analysing biochemical pathways, which uni¯es the qualita- tive, stochastic and continuous paradigms. Each perspective adds its con- tribution to the understanding of the system, thus the three approaches do not compete, but complement each other. We illustrate our approach by applying it to an extended model of the three stage cascade, which forms the core of the ERK signal transduction pathway. Consequently our focus is on transient behaviour analysis. We demonstrate how quali- tative descriptions are abstractions over stochastic or continuous descrip- tions, and show that the stochastic and continuous models approximate each other. Although our framework is based on Petri nets, it can be applied more widely to other formalisms which are used to model and analyse biochemical networks

Model-based dependability analysis : state-of-the-art, challenges and future outlook

Abstract: Over the past two decades, the study of model-based dependability analysis has gathered significant research interest. Different approaches have been developed to automate and address various limitations of classical dependability techniques to contend with the increasing complexity and challenges of modern safety-critical system. Two leading paradigms have emerged, one which constructs predictive system failure models from component failure models compositionally using the topology of the system. The other utilizes design models - typically state automata - to explore system behaviour through fault injection. This paper reviews a number of prominent techniques under these two paradigms, and provides an insight into their working mechanism, applicability, strengths and challenges, as well as recent developments within these fields. We also discuss the emerging trends on integrated approaches and advanced analysis capabilities. Lastly, we outline the future outlook for model-based dependability analysis

Building on the DEPLOY Legacy: Code Generation and Simulation

The RODIN, and DEPLOY projects laid solid foundations for further theoretical, and practical (methodological and tooling) advances with Event-B. Our current interest is the co-simulation of cyber-physical systems using Event-B. Using this approach we aim to simulate various features of the environment separately, in order to exercise deployable code. This paper has two contributions, the first is the extension of the code generation work of DEPLOY, where we add the ability to generate code from Event-B state-machine diagrams. The second describes how we may use code, generated from state-machines, to simulate the environment, and simulate concurrently executing state-machines, in a single task. We show how we can instrument the code to guide the simulation, by controlling the relative rate that non-deterministic transitions are traversed in the simulation.Comment: In Proceedings of DS-Event-B 2012: Workshop on the experience of and advances in developing dependable systems in Event-B, in conjunction with ICFEM 2012 - Kyoto, Japan, November 13, 201

Building on the DEPLOY legacy: code generation and simulation

The RODIN, and DEPLOY projects have laid solid foundations for further theoretical, and practical (methodological and tooling) advances with Event-B; we investigated code generation for embedded, multi-tasking systems. This work describes activities from a follow-on project, ADVANCE; where our interest is co-simulation of cyber-physical systems. We are working to better understand the issues arising in a development when modelling with Event-B, and animating with ProB, in tandem with a multi-simulation strategy. With multi-simulation we aim to simulate various features of the environment separately, in order to exercise the deployable code. This paper has two contributions, the first is the extension of the code generation work of DEPLOY, where we add the ability to generate code from Event-B state-machine diagrams. The second describes how we may use code, generated from state-machines, to simulate the environment, and simulate concurrently executing state-machines, in a single task. We show how we can instrument the code to guide the simulation, by controlling the relative rate that non-deterministic transitions are traversed in the simulation

Performance modelling for system-level design

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Learning Concise Models from Long Execution Traces

Abstract models of system-level behaviour have applications in design exploration, analysis, testing and verification. We describe a new algorithm for automatically extracting useful models, as automata, from execution traces of a HW/SW system driven by software exercising a use-case of interest. Our algorithm leverages modern program synthesis techniques to generate predicates on automaton edges, succinctly describing system behaviour. It employs trace segmentation to tackle complexity for long traces. We learn concise models capturing transaction-level, system-wide behaviour--experimentally demonstrating the approach using traces from a variety of sources, including the x86 QEMU virtual platform and the Real-Time Linux kernel

Process Modeling for Simulation

This paper discusses shortfalls in relation to the requirements gathering phases of simulation. While many developments have taken place around supporting the model coding task of simulation, there are few tools available to assist in the requirements gathering phase. This is surprising as it has been reported by several researchers that the requirements phase can absorb twice as much resources as the coding phase. There are numerous process modeling tools available (over 100) that can and have been used to support the requirements phase of simulation. This paper provides a selective review of some of the most important in relation to simulation. A conclusion from this review is that none of the tools available adequately supports the requirements gathering phase of simulation. It is proposed that a process modeling tool be developed specifically to support simulation requirements gathering. The design objectives in the development of the tool are: (1) it should be capable of capturing a detailed description of a discrete event system; (2) it should have a low modeling burden and therefore be capable of being used by non-specialists; (3) it should present modeling information at a high semantic level so that manufacturing personnel can rationalize with it; (4) it should have good visualization capabilities; (5) it should support project teamwork. Based on these design objectives a proposed simulation process modeling tool called simulation activity diagrams (SAD) is presented