Designing robust software systems through parametric markov chain synthesis

Conference item

We present a method for the synthesis of software system designs that satisfy strict quality requirements, are Paretooptimal with respect to a set of quality optimisation criteria, and are robust to variations in the system parameters. To this end, we model the design space of the system under development as a parametric continuous-time Markov chain (pCTMC) with discrete and continuous parameters that correspond to alternative system architectures and to the ranges of possible values for configuration parameters, respectively. Given this pCTMC and required tolerance levels for the configuration parameters, our method produces a sensitivity-aware Pareto-optimal set of designs, which allows the modeller to inspect the ranges of quality attributes induced by these tolerances, thus enabling the effective selection of robust designs. Through application to two systems from different domains, we demonstrate the ability of our method to synthesise robust designs with a wide spectrum of useful tradeoffs between quality attributes and sensitivity.

Authors: Kwiatkowska, M; Calinescu, R; Ceska, M; Gerasimou, S; Paoletti, N

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Institute of Electrical and Electronics Engineers
• Host title: IEEE International Conference on Software Architecture (ICSA 2017)
• Journal: IEEE International Conference on Software Architecture (ICSA 2017).
• Publication date: 2017-05-01
• Acceptance date: 2017-03-10
• DOI: 10.1109/ICSA.2017.16
• Keywords: software performance and reliability engineering; probabilistic model synthesis; multi-objective optimisation