A model-driven approach to broaden the detection of software performance antipatterns at runtime

Antinisca Di Marco
(University of L'Aquila)
Catia Trubiani
(University of L'Aquila)

Performance antipatterns document bad design patterns that have negative influence on system performance. In our previous work we formalized such antipatterns as logical predicates that predicate on four views: (i) the static view that captures the software elements (e.g. classes, components) and the static relationships among them; (ii) the dynamic view that represents the interaction (e.g. messages) that occurs between the software entities elements to provide the system functionalities; (iii) the deployment view that describes the hardware elements (e.g. processing nodes) and the mapping of the software entities onto the hardware platform; (iv) the performance view that collects specific performance indices. In this paper we present a lightweight infrastructure that is able to detect performance antipatterns at runtime through monitoring. The proposed approach precalculates such predicates and identifies antipatterns whose static, dynamic and deployment sub-predicates are validated by the current system configuration and brings at runtime the verification of performance sub-predicates. The proposed infrastructure leverages model-driven techniques to generate probes for monitoring the performance sub-predicates and detecting antipatterns at runtime.

In Bara Buhnova, Lucia Happe and Jan Kofroň: Proceedings 11th International Workshop on Formal Engineering approaches to Software Components and Architectures (FESCA 2014), Grenoble, France, 12th April 2014, Electronic Proceedings in Theoretical Computer Science 147, pp. 77–92.
Published: 2nd April 2014.

ArXived at: http://dx.doi.org/10.4204/EPTCS.147.6 bibtex PDF
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