By the same authors

Designing Robust Software Systems through Parametric Markov Chain Synthesis

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Publication details

Title of host publicationIEEE International Conference on Software Architecture (ICSA 2017)
DateAccepted/In press - 13 Feb 2017
DatePublished (current) - Apr 2017
Number of pages10
Original languageEnglish


We present a method for the synthesis of software system designs that satisfy strict quality requirements, are Pareto-optimal 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.

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