A Temporal Model for Interactive Diagnosis of Adaptive Systems

Abstract

Kicking off the DiverSE coffee for this year, we’re happy to announce that Ludovic Mouline will be presenting his latest accepted paper on improving interactive diagnosis of adaptive systems using temporal models. The presentation is held this Thursday in room Aurigny at 1 pm. Enters Ludovic: The evolving complexity of adaptive systems impairs our ability to deliver anomaly-free solutions. Fixing these systems require a deep understanding on the reasons behind decisions which led to faulty or suboptimal system states. Developers thus need diagnosis support that trace system states to the previous circumstances –targeted requirements, input context– that had resulted in these decisions. However, the lack of efficient temporal representation limits the tracing ability of current approaches. To tackle this problem, we describe a novel temporal data model to represent, store and query decisions as well as their relationship with the knowledge (context, requirements, and actions). We validate our approach through a use case based on the smart grid at Luxembourg.