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Registered user since Wed 30 Oct 2019
Contributions
Journal-first Papers
Wed 12 Oct 2022 16:00 - 16:20 at Gold A - Technical Session 20 - Web, Cloud, Networking Chair(s): Karine Even-MendozaPerformance models have been used in the past to understand the performance characteristics of software systems. However, the identification of performance criticalities is still an open challenge, since there might be several system components contributing to the overall system performance. This work combines two different areas of research to improve the process of interpreting model-based performance analysis results: (i) software performance engineering that provides the ground for the evaluation of the system’s performance; (ii) mutation-based techniques that nicely supports the experimentation of changes in performance models and contribute to a more systematic assessment of performance indices. We propose mutation operators for specific performance models, i.e., queueing networks, that resemble changes commonly made by designers when exploring the properties of a system’s performance. Our approach consists in introducing a mutation-based approach that generates a set of mutated queueing network models. The performance of these mutated networks is compared to that of the original network to better understand the effect of variations in the different components of the system. A set of benchmarks is adopted to show how the technique can be used to get a deeper understanding of the performance characteristics of software systems.
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