Model-Centric, Context-Aware Software Adaptation

Software must be constantly adapted to changing requirements. The time scale, abstraction level and granularity of adaptations may vary from short-term, fine-grained adaptation to long-term, coarse-grained evolution. Fine-grained, dynamic and context-dependent adaptations can be particularly difficult to realize in long-lived, large-scale software systems. We argue that, in order to effectively and efficiently deploy such changes, adaptive applications must be built on an infrastructure that is not just model-driven, but is both model-centric and context-aware. Specifically, this means that high-level, causally-connected models of the application and the software infrastructure itself should be available at run-time, and that changes may need to be scoped to the run-time execution context. We first review the dimensions of software adaptation and evolution, and then we show how model-centric design can address the adaptation needs of a variety of applications that span these dimensions. We demonstrate through concrete examples how model-centric and context-aware designs work at the level of application interface, programming language and runtime. We then propose a research agenda for a model-centric development environment that supports dynamic software adaptation and evolution.

Context-Oriented Programming

Context-dependent behavior is becoming increasingly important for a wide range of application domains, from pervasive computing to common business applications. Unfortunately, mainstream programming languages do not provide mechanisms that enable software entities to adapt their behavior dynamically to the current execution context. This leads developers to adopt convoluted designs to achieve the necessary runtime flexibility. We propose a new programming technique called Context-oriented Programming (COP) which addresses this problem. COP treats context explicitly, and provides mechanisms to dynamically adapt behavior in reaction to changes in context, even after system deployment at runtime. In this paper we lay the foundations of COP, show how dynamic layer activation enables multi-dimensional dispatch, illustrate the application of COP by examples in several language extensions, and demonstrate that COP is largely independent of other commitments to programming style.

The role of the human posterior parietal cortex in memory-guided saccade execution: a double-pulse transcranial magnetic stimulation study

The present study investigated the role of the right posterior parietal cortex (PPC) in the triggering of memory-guided saccades by means of double-pulse transcranial magnetic stimulation (dTMS). Shortly before saccade onset, dTMS with different interstimulus intervals (ISI; 35, 50, 65 or 80 ms) was applied. For contralateral saccades, dTMS significantly decreased saccadic latency with an ISI of 80 ms and increased saccadic gain with an ISI of 65 and 80 ms. Together with the findings of a previous study during frontal eye field (FEF) stimulation the present results demonstrate similarities and differences between both regions in the execution of memory-guided saccades. Firstly, dTMS facilitates saccade triggering in both regions, but the timing is different. Secondly, dTMS over the PPC provokes a hypermetria of contralateral memory-guided saccades that was not observed during FEF stimulation. The results are discussed within the context of recent neurophysiological findings in monkeys.