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MBPeT – A Model-Based Performance Testing Tool

Fredrik Abbors, Tanwir Ahmad, Dragos Truscan, Ivan Porres, MBPeT – A Model-Based Performance Testing Tool. In: Amir Alimohammad, Petre Dini (Eds.), 4th International Conference on Advances in System Testing and Validation Lifecycle, 1–8, IARIA, 2012.

Abstract:

In recent years, cloud computing has become
increasingly common. Verifying that applications deployed in the cloud meet their performance requirements is not simple. There are three different techniques for performance
evaluation: analytical modeling, simulation, and measurement. While analytical modeling and simulation are good techniques for getting an early performance estimation, they rely on an abstract representation of the system and leave out details related for instance to the system configuration. Such details are problematic to model or simulate, however they can be the source of the bottlenecks in the deployed system. In this paper, we present a model-based performance testing tool that measures the performance on web applications and services using the measurement technique. The tool uses models to generate workload which is then applied to the system in real-time and it measures different performance indicators. The models are defined using probabilistic timed automata and they describe how different user types interact with the system. We describe how load is generated from the models and the
features of the tool. The utility of the tool is demonstrated by applying to a WebDav case study.

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BibTeX entry:

@INPROCEEDINGS{inpAbAhTrPo12a,
  title = {MBPeT – A Model-Based Performance Testing Tool},
  booktitle = {4th International Conference on Advances in System Testing and Validation Lifecycle},
  author = {Abbors, Fredrik and Ahmad, Tanwir and Truscan, Dragos and Porres, Ivan},
  editor = {Alimohammad, Amir and Dini, Petre},
  publisher = {IARIA},
  pages = {1–8},
  year = {2012},
  keywords = {Load Generation. Model-Based Performance Testing. Monitoring. Probabilistic Timed Automata. Models.},
}

Belongs to TUCS Research Unit(s): Software Engineering Laboratory (SE Lab)

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