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

Tutkimustuotos: Artikkeli kirjassa/raportissa/konferenssijulkaisussa › Konferenssiartikkeli › Tieteellinen › vertaisarvioitu

3 Sitaatiot (Scopus)

1 Lataukset (Pure)

Abstrakti

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.

Alkuperäiskieli	Ei tiedossa
Otsikko	Proceedings of the 9th International Conference on Software Engineering and Application
Toimittajat	Andreas Holzinger, Therese Libourel, Leszek Maciaszek, Stephen Mellor
Kustantaja	SCITEPRESS Science And Technology Publications
Sivut	14–25
ISBN (painettu)	978-989-758-036-9
DOI - pysyväislinkit	https://doi.org/10.5220/0005002200140025
Tila	Julkaistu - 2014
OKM-julkaisutyyppi	A4 Artikkeli konferenssijulkaisuussa
Tapahtuma	conference; 2014-08-29; 2014-08-31 - Vienna Kesto: 29 elokuuta 2014 → 31 elokuuta 2014

Konferenssi

Konferenssi	conference; 2014-08-29; 2014-08-31
Ajanjakso	29/08/14 → 31/08/14

Keywords

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

Pääsy asiakirjaan

10.5220/0005002200140025

paper.pdf

http://www.scitepress.org/

2 Päättynyt

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

Viittausmuodot

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

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

@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 = "null ; 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. julkaisussa A Holzinger, T Libourel, L Maciaszek & S Mellor (toim), Proceedings of the 9th International Conference on Software Engineering and Application. SCITEPRESS Science And Technology Publications, Sivut 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. toim. / Andreas Holzinger; Therese Libourel; Leszek Maciaszek; Stephen Mellor. SCITEPRESS Science And Technology Publications, 2014. s. 14–25.

Tutkimustuotos: Artikkeli kirjassa/raportissa/konferenssijulkaisussa › Konferenssiartikkeli › Tieteellinen › vertaisarvioitu

TY - GEN

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

AU - Abbors, Fredrik

AU - Truscan, Dragos

AU - Ahmad, Tanwir

PY - 2014

Y1 - 2014

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.

KW - Log file analysis

KW - Performance testing

KW - Probabilistic Timed Automata

KW - Workload model generation,

KW - Log file analysis

KW - Performance testing

KW - Probabilistic Timed Automata

KW - Workload model generation,

KW - Log file analysis

KW - Performance testing

KW - Probabilistic Timed Automata

KW - Workload model generation,

U2 - 10.5220/0005002200140025

DO - 10.5220/0005002200140025

M3 - Konferensbidrag

SN - 978-989-758-036-9

SP - 14

EP - 25

BT - Proceedings of the 9th International Conference on Software Engineering and Application

A2 - Holzinger, Andreas

A2 - Libourel, Therese

A2 - Maciaszek, Leszek

A2 - Mellor, Stephen

PB - SCITEPRESS Science And Technology Publications

Y2 - 29 August 2014 through 31 August 2014

ER -

An Automated Approach for CreatingWorkload Models From Server Log Data

Abstrakti

Konferenssi

Keywords

Pääsy asiakirjaan

Projektit

N4S: Need for Speed

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

Viittausmuodot