An Automated Approach for CreatingWorkload Models From Server Log Data

Fredrik Abbors; Dragos Truscan; Tanwir Ahmad

doi:10.5220/0005002200140025

An Automated Approach for CreatingWorkload Models From Server Log Data

Fredrik Abbors, Dragos Truscan, Tanwir Ahmad

Forskningsoutput: Kapitel i bok/konferenshandling › Publicerad konferensartikel › Vetenskaplig › Peer review

3 Citeringar (Scopus)

43 Nedladdningar (Pure)

Sammanfattning

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. 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.

Originalspråk	Odefinierat/okänt
Titel på värdpublikation	Proceedings of the 9th International Conference on Software Engineering and Application
Redaktörer	Andreas Holzinger, Therese Libourel, Leszek Maciaszek, Stephen Mellor
Förlag	SCITEPRESS Science And Technology Publications
Sidor	14–25
ISBN (tryckt)	978-989-758-036-9
DOI	https://doi.org/10.5220/0005002200140025
Status	Publicerad - 2014
MoE-publikationstyp	A4 Artikel i en konferenspublikation
Evenemang	conference; 2014-08-29; 2014-08-31 - Vienna Varaktighet: 29 aug. 2014 → 31 aug. 2014

Konferens

Konferens	conference; 2014-08-29; 2014-08-31
Period	29/08/14 → 31/08/14

Nyckelord

Log file analysis
Performance testing
Probabilistic Timed Automata
Workload model generation,

Åtkomst av dokument

10.5220/0005002200140025

paper.pdf

http://www.scitepress.org/

N4S: Need for Speed
Porres Paltor, I. (Ansvarig forskare), Nybom, K. (CoI), Truscan, D. (CoI), Ashraf, A. (CoI), Troubitsyna, E. (CoI), Byholm, B. (CoI), Rauf, I. M. (CoI) & Ahmad, T. (CoI)
01/01/14 → 31/12/16
Projekt: Företag/Business Finland
PAM: Practical Applications of Model-based technologies to continuous integration & testing methodologies
Truscan, D. (Ansvarig forskare), Ahmad, T. (CoI), Iqbal, J. (Ansvarig forskare), Porres Paltor, I. (CoPI) & Siavashi, F. (CoI)
01/01/12 → 31/12/15
Projekt: Företag/Business Finland

Citera det här

Abbors, F., Truscan, D., & Ahmad, T. (2014). An Automated Approach for CreatingWorkload Models From Server Log Data. I A. Holzinger, T. Libourel, L. Maciaszek, & S. Mellor (Red.), Proceedings of the 9th International Conference on Software Engineering and Application (s. 14–25). SCITEPRESS Science And Technology Publications. https://doi.org/10.5220/0005002200140025

@inproceedings{0f02e2edd68641668f58bffcaf579765,

title = "An Automated Approach for CreatingWorkload Models From Server Log Data",

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. 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.",

keywords = "Log file analysis, Performance testing, Probabilistic Timed Automata, Workload model generation,, Log file analysis, Performance testing, Probabilistic Timed Automata, Workload model generation,, Log file analysis, Performance testing, Probabilistic Timed Automata, Workload model generation,",

author = "Fredrik Abbors and Dragos Truscan and Tanwir Ahmad",

year = "2014",

doi = "10.5220/0005002200140025",

language = "Odefinierat/ok{\"a}nt",

isbn = "978-989-758-036-9",

pages = "14–25",

editor = "Andreas Holzinger and Therese Libourel and Leszek Maciaszek and Stephen Mellor",

booktitle = "Proceedings of the 9th International Conference on Software Engineering and Application",

publisher = "SCITEPRESS Science And Technology Publications",

note = "conference; 2014-08-29; 2014-08-31 ; Conference date: 29-08-2014 Through 31-08-2014",

}

Abbors, F, Truscan, D & Ahmad, T 2014, An Automated Approach for CreatingWorkload Models From Server Log Data. i A Holzinger, T Libourel, L Maciaszek & S Mellor (red), Proceedings of the 9th International Conference on Software Engineering and Application. SCITEPRESS Science And Technology Publications, s. 14–25, conference; 2014-08-29; 2014-08-31, 29/08/14. https://doi.org/10.5220/0005002200140025

An Automated Approach for CreatingWorkload Models From Server Log Data. / Abbors, Fredrik; Truscan, Dragos ; Ahmad, Tanwir.
Proceedings of the 9th International Conference on Software Engineering and Application. red. / Andreas Holzinger; Therese Libourel; Leszek Maciaszek; Stephen Mellor. SCITEPRESS Science And Technology Publications, 2014. s. 14–25.

Forskningsoutput: Kapitel i bok/konferenshandling › Publicerad konferensartikel › Vetenskaplig › Peer review

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T1 - An Automated Approach for CreatingWorkload Models From Server Log Data

AU - Abbors, Fredrik

AU - Truscan, Dragos

AU - Ahmad, Tanwir

PY - 2014

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N2 - 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. 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.

AB - 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. 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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KW - Performance testing

KW - Probabilistic Timed Automata

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KW - Performance testing

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KW - Performance testing

KW - Probabilistic Timed Automata

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T2 - conference; 2014-08-29; 2014-08-31

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ER -

An Automated Approach for CreatingWorkload Models From Server Log Data

Sammanfattning

Konferens

Nyckelord

Åtkomst av dokument

Projekt

N4S: Need for Speed

PAM: Practical Applications of Model-based technologies to continuous integration & testing methodologies

Citera det här