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An Automated Approach for Creating Workload Models From Server Log Data

Fredrik Abbors, Dragos Truscan, Tanwir Ahmad, An Automated Approach for Creating Workload Models From Server Log Data. In: Holzinger Andreas, Libourel Therese, Maciaszek Leszek, Mellor Stephen (Eds.), Proceedings of the 9th International Conference on Software Engineering and Applications, 14–25, Scitepress, 2014.

http://dx.doi.org/10.5220/0005002200140025

Abstract:

We present a tool-supported approach for creating workload models from historical web access log data. The resulting workload models are stochastic, represented as Probabilistic Timed Automata (PTA), and describe how users interact with the system. Such models allow one to analyze different user profiles and to mimic real user behavior as closely as possible when generating workload. We provide an experiment to validate the approach.

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BibTeX entry:

@INPROCEEDINGS{inpFrDrTa14a,
  title = {An Automated Approach for Creating Workload Models From Server Log Data},
  booktitle = {Proceedings of the 9th International Conference on Software Engineering and Applications},
  author = {Abbors, Fredrik and Truscan, Dragos and Ahmad, Tanwir},
  editor = {Andreas, Holzinger and Therese, Libourel and Leszek, Maciaszek and Stephen, Mellor},
  publisher = {Scitepress},
  pages = {14–25},
  year = {2014},
  keywords = {Workload model generation, Log file analysis, Performance testing, Probabilistic Timed Automata},
  ISSN = {978-989-758-036-9},
}

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

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