2013-04-23: Seminar Rushby (SRI International) on The Challenge of High-Assurance Software

It is difficult to build complex systems that (almost) never go (badly) wrong, yet this is what we expect of airplanes and pacemakers and the phone system. In essence, we have to anticipate everything that could fail or go wrong, develop countermeasures, and then provide compelling evidence that we have done all this correctly. Dr Rushby outline's some of the intellectual challenges in construction of suitable evidence, particularly as applied to software.

2013-04-19: Seminar Reeves (University of Waikato) on Modelling Safety Properties of Interactive Medical Systems

Formally modelling the software functionality and interactivity of safety-critical devices allows us to prove properties about their behaviours and be certain that they will respond to user interaction correctly. In domains such as medical environments, where many different devices may be used, it is equally important to ensure that all devices used adhere to a set of safety, and other, principles designed for that environment.

2013-04-09: Seminar Abramsky (Oxford University) on Coalgebraic Analysis of Subgame-perfect Equilibria in Infinite Games without Discounting
We present a novel coalgebraic formulation of infinite extensive games. We define both the game trees and the strategy profiles by possibly infinite systems of corecursive equations.

2013-03-20: Seminar Babar (Lancaster University) on Experiences from Human-Centric Software Engineering Research
One of our main research goals is to empirically understand how software engineers work with technologies and interact with each otters when developing software. To this end, we have conducted several dozens of empirical studies in industrial and academic environments.

2013-03-19: Seminar Stolzenburg (Harz University) on Neural Learning with Applications in Object Recognition and Harmony Perception
The fields of neural computation and artificial neural networks have developed much in the last decades. Since technical, physical, and also cognitive processes evolve in time, neural networks should be considered, which allow us to model the synthesis and analysis of continuous and possibly periodic processes in time besides computing discrete classification functions.