A synthesis of logic and bio-inspired techniques in the design of dependable systems. (2016)

• Record Type: Journal Article
• Authors: Papadopoulos, Yiannis; Walker, Martin; Parker, David; Sharvia, Septavera; Bottaci, Leonardo; Kabir, Sohag; Azevedo, Luis; Sorokos, Ioannis
• Is Part Of: Annual reviews in control. Volume 41(2016)
• Page Start: 170
• Page End: 182
• Publication Date: 2016
• Subjects: Dependability -- Safety integrity levels -- Genetic algorithms -- MBSA -- HiP-HOPS; Automatic control -- Periodicals; Periodicals; 629.805
• DOI: 10.1016/j.arcontrol.2016.04.008
• Languages: English
• ISSNs: 1367-5788

Abstract

Abstract: Much of the development of model-based design and dependability analysis in the design of dependable systems, including software intensive systems, can be attributed to the application of advances in formal logic and its application to fault forecasting and verification of systems. In parallel, work on bio-inspired technologies has shown potential for the evolutionary design of engineering systems via automated exploration of potentially large design spaces. We have not yet seen the emergence of a design paradigm that effectively combines these two techniques, schematically founded on the two pillars of formal logic and biology, from the early stages of, and throughout, the design lifecycle. Such a design paradigm would apply these techniques synergistically and systematically to enable optimal refinement of new designs which can be driven effectively by dependability requirements. The paper sketches such a model-centric paradigm for the design of dependable systems, presented in the scope of the HiP-HOPS tool and technique, that brings these technologies together to realise their combined potential benefits. The paper begins by identifying current challenges in model-based safety assessment and then overviews the use of meta-heuristics at various stages of the design lifecycle covering topics that span from allocation of dependability requirements, through dependability analysis, to multi-objective optimisation of system architectures and maintenance schedules.