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Erschienen in:
BPMN 2.0 and the Service Interaction Patterns: Can We Support Them All? Kapitel lesen Erstes Kapitel lesen

2015 | OriginalPaper | Buchkapitel

Mining Web Server Logs for Creating Workload Models

verfasst von : Fredrik Abbors, Dragos Truscan, Tanwir Ahmad

Erschienen in: Software Technologies

Verlag: Springer International Publishing

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Abstract

We present a tool-supported approach where we used data mining techniques for automatically inferring workload models from historical web access log data. The workload models are represented as Probabilistic Timed Automata (PTA) and describe how users interact with the system. Via their stochastic nature, PTAs have more advantages over traditional approaches which simply playback scripted or pre-recorded traces: they are easier to create and maintain and achieve higher coverage of the tested application. The purpose of these models is to mimic real-user behavior as closely as possible when generating load. To show the validity and applicability of our proposed approach, we present a few experiments. The results show, that the workload models automatically derived from web server logs are able to generate similar load with the one applied by real-users on the system and that they can be used as the starting point for performance testing process.

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Vorheriges Kapitel Model Transformation by Example Driven ATL Transformation Rules Development Using Model Differences
Nächstes Kapitel New Flexible Architectures for Reconfigurable Wireless Sensor Networks
Fußnoten
1
Our approach uses IP-addresses for user classification since the UserId is only available for authenticated users and usually not present in the log.
 
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Metadaten
Titel
Mining Web Server Logs for Creating Workload Models
verfasst von
Fredrik Abbors
Dragos Truscan
Tanwir Ahmad
Copyright-Jahr
2015
Buch
Software Technologies

Print ISBN: 978-3-319-25578-1

Electronic ISBN: 978-3-319-25579-8

Copyright-Jahr: 2015

DOI
https://doi.org/10.1007/978-3-319-25579-8_8