Filling the gap: A tool to automate parameter estimation for software performance models

Weikun Wang; Juan F. Pérez; Giuliano Casale

doi:10.1145/2804371.2804379

Filling the gap: A tool to automate parameter estimation for software performance models

Weikun Wang, Juan F. Pérez, Giuliano Casale

Research output: Chapter in Book/Report › Conference contribution

7 Scopus citations

Abstract

Software performance engineering heavily relies on application and resource models that enable the prediction of Quality-of-Service metrics. Critical to these models is the accuracy of their parameters, the value of which can change with the application and the resources where it is deployed. In this paper we introduce the Filling-the-gap (FG) tool, which automates the parameter estimation of application performance models. This tool implements a set of statistical routines to estimate the parameters of performance models, which are automatically executed using monitoring information kept in a local database.

Translated title of the contribution	Llenando el vacío: Una herramienta para automatizar la estimación de parámetros para modelos de rendimiento de software
Original language	English (US)
Title of host publication	1st International Workshop on Quality-Aware DevOps, QUDOS 2015 - Proceedings
Publisher	Association for Computing Machinery
Pages	31-32
Number of pages	2
ISBN (Electronic)	9781450338172
DOIs	https://doi.org/10.1145/2804371.2804379
State	Published - Sep 1 2015
Externally published	Yes
Event	1st International Workshop on Quality-Aware DevOps, QUDOS 2015 - Bergamo, Italy Duration: Sep 1 2015 → …

Conference

Conference	1st International Workshop on Quality-Aware DevOps, QUDOS 2015
Country/Territory	Italy
City	Bergamo
Period	9/1/15 → …

All Science Journal Classification (ASJC) codes

Software

Access to Document

10.1145/2804371.2804379

Cite this

@inproceedings{e7522bdfcf334b5bb5f315245ae5a3ac,

title = "Filling the gap: A tool to automate parameter estimation for software performance models",

abstract = "Software performance engineering heavily relies on application and resource models that enable the prediction of Quality-of-Service metrics. Critical to these models is the accuracy of their parameters, the value of which can change with the application and the resources where it is deployed. In this paper we introduce the Filling-the-gap (FG) tool, which automates the parameter estimation of application performance models. This tool implements a set of statistical routines to estimate the parameters of performance models, which are automatically executed using monitoring information kept in a local database.",

author = "Weikun Wang and P{\'e}rez, {Juan F.} and Giuliano Casale",

year = "2015",

month = sep,

day = "1",

doi = "10.1145/2804371.2804379",

language = "English (US)",

pages = "31--32",

booktitle = "1st International Workshop on Quality-Aware DevOps, QUDOS 2015 - Proceedings",

publisher = "Association for Computing Machinery",

address = "United States",

note = "1st International Workshop on Quality-Aware DevOps, QUDOS 2015 ; Conference date: 01-09-2015",

}

Wang, W, Pérez, JF & Casale, G 2015, Filling the gap: A tool to automate parameter estimation for software performance models. in 1st International Workshop on Quality-Aware DevOps, QUDOS 2015 - Proceedings. Association for Computing Machinery, pp. 31-32, 1st International Workshop on Quality-Aware DevOps, QUDOS 2015, Bergamo, Italy, 9/1/15. https://doi.org/10.1145/2804371.2804379

TY - GEN

T1 - Filling the gap

T2 - 1st International Workshop on Quality-Aware DevOps, QUDOS 2015

AU - Wang, Weikun

AU - Pérez, Juan F.

AU - Casale, Giuliano

PY - 2015/9/1

Y1 - 2015/9/1

N2 - Software performance engineering heavily relies on application and resource models that enable the prediction of Quality-of-Service metrics. Critical to these models is the accuracy of their parameters, the value of which can change with the application and the resources where it is deployed. In this paper we introduce the Filling-the-gap (FG) tool, which automates the parameter estimation of application performance models. This tool implements a set of statistical routines to estimate the parameters of performance models, which are automatically executed using monitoring information kept in a local database.

AB - Software performance engineering heavily relies on application and resource models that enable the prediction of Quality-of-Service metrics. Critical to these models is the accuracy of their parameters, the value of which can change with the application and the resources where it is deployed. In this paper we introduce the Filling-the-gap (FG) tool, which automates the parameter estimation of application performance models. This tool implements a set of statistical routines to estimate the parameters of performance models, which are automatically executed using monitoring information kept in a local database.

UR - http://www.scopus.com/inward/record.url?scp=84960411384&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84960411384&partnerID=8YFLogxK

U2 - 10.1145/2804371.2804379

DO - 10.1145/2804371.2804379

M3 - Conference contribution

AN - SCOPUS:84960411384

SP - 31

EP - 32

BT - 1st International Workshop on Quality-Aware DevOps, QUDOS 2015 - Proceedings

PB - Association for Computing Machinery

Y2 - 1 September 2015

ER -

Filling the gap: A tool to automate parameter estimation for software performance models

Abstract

Conference

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Fingerprint

Cite this