Biblio

Filters: Author is Marta Kwiatkowska, University of Oxford  [Clear All Filters]
2016-10-24
2016-12-14
2015-11-17
Zhenqi Huang, University of Illinois at Urbana-Champaign, Chuchu Fan, University of Illinois at Urbana-Champaign, Alexandru Mereacre, University of Oxford, Sayan Mitra, University of Illinois at Urbana-Champaign, Marta Kwiatkowska, University of Oxford.  2015.  Simulation-based Verification of Cardiac Pacemakers with Guaranteed Coverage. Special Issue of IEEE Design and Test. 32(5)

Design and testing of pacemaker is challenging because of the need to capture the interaction between the physical processes (e.g. voltage signal in cardiac tissue) and the embedded software (e.g. a pacemaker). At the same time, there is a growing need for design and certification methodologies that can provide quality assurance for the embedded software. We describe recent progress in simulation-based techniques that are capable of ensuring guaranteed coverage. Our methods employ discrep- ancy functions, which impose bounds on system dynamics, and proceed through iteratively constructing over-approximations of the reachable set of states. We are able to prove time bounded safety or produce counterexamples. We illustrate the techniques by analyzing a family of pacemaker designs against time duration requirements and synthesize safe parameter ranges. We conclude by outlining the potential uses of this technology to improve the safety of medical device designs.

Zhenqi Huang, University of Illinois at Urbana-Champaign, Chuchu Fan, University of Illinois at Urbana-Champaign, Alexandru Mereacre, University of Oxford, Sayan Mitra, University of Illinois at Urbana-Champaign, Marta Kwiatkowska, University of Oxford.  2014.  Invariant Verification of Nonlinear Hybrid Automata Networks of Cardiac Cells. 26th International Conference on Computer Aided Verification (CAV 2014).

Verification algorithms for networks of nonlinear hybrid automata (HA) can aid us understand and control biological processes such as cardiac arrhythmia, formation of memory, and genetic regulation. We present an algorithm for over-approximating reach sets of networks of nonlinear HA which can be used for sound and relatively complete invariant checking. First, it uses automatically computed input-to-state discrepancy functions for the individual automata modules in the network A for constructing a low-dimensional model M. Simulations of both A and M are then used to compute the reach tubes for A. These techniques enable us to handle a challenging verification problem involving a network of cardiac cells, where each cell has four continuous variables and 29 locations. Our prototype tool can check bounded-time invariants for networks with 5 cells (20 continuous variables, 295 locations) typically in less than 15 minutes for up to reasonable time horizons. From the computed reach tubes we can infer biologically relevant properties of the network from a set of initial states.