Inferring extended finite state machine models from software executions

The ability to reverse-engineer models of software behaviour is valuable for a wide range of software maintenance, validation and verification tasks. Current reverse-engineering techniques focus either on control-specific behaviour (e.g., in the form of Finite State Machines), or data-specific behaviour (e.g., as pre / post-conditions or invariants). However, typical software behaviour is usually a product of the two; models must combine both aspects to fully represent the software’s operation. Extended Finite State Machines (EFSMs) provide such a model. Although attempts have been made to infer EFSMs, these have been problematic. The models inferred by these techniques can be non-deterministic, the inference algorithms can be inflexible, and only applicable to traces with specific characteristics. This paper presents a novel EFSM inference technique that addresses the problems of inflexibility and non-determinism. It also adapts an experimental technique from the field of Machine Learning to evaluate EFSM inference techniques, and applies it to three diverse software systems.     

Playing on a holo-stage: towards the interaction between real and virtual performers

This paper presents a number of ongoing projects that will be valuable to the development of technologies for digital theatre and performance. This paper describes an EU ACTS project called RESOLV which develops an integrated system to capture real 3D environments using laser and video. Current research on motion tracking, statistical behaviour modelling and simulation is presented, and possible applications, both for visual augmentation and audio generation, are discussed. The projects presented were not originally designed in the domain of theatre and performance, however their results and output seem to be well suited to be applied in this area.     

Influence of Pluronic coating formulation on iron oxide nanoparticle transport in natural and oil-impacted sandy aquifer media

Targeted delivery of nanoparticles has the potential to enhance remediation and characterization of sites contaminated with non-aqueous phase liquids (NAPLs) by ensuring delivery of treatment or contrast agents to the NAPL/water interface. For a targeted delivery technique to be successful, nanoparticles must be capable of transporting through porous media and binding to NAPLs under relevant geological conditions. In this study, successful targeted delivery of nanoparticles to sandy aquifer material mixed with crude oil was achieved using an active targeting technique based on an amphiphilic polymer coating. It was determined that the molecular structure and concentration of the nanoparticle coating greatly influenced the recovery of nanoparticles injected into saturated columns. Coatings with longer polymer molecules and lower polymer concentrations reduced recovery, and the nanoparticle coating formulation could be adjusted to improve transport while maintaining targeted binding behaviour. This study demonstrated that nanoparticle retention in oil-impacted sand exceeded that of clean sand in flow through experiments, indicating that a nanoparticle targeted delivery strategy for soil contaminated with LNAPLs such as crude oil is possible under the experimental conditions explored.