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Reliability analysis using weighted combinational models for web-based software

Authors:

Chao-Jung Hsu,

Chin-Yu HuangAuthors Info & Claims

WWW '09: Proceedings of the 18th international conference on World wide web

Pages 1131 - 1132

https://doi.org/10.1145/1526709.1526892

Published: 20 April 2009 Publication History

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Abstract

In the past, some researches suggested that engineers can use combined software reliability growth models (SRGMs) to obtain more accurate reliability prediction during testing. In this paper, three weighted combinational models, namely, equal, linear, and nonlinear weight, are proposed for reliability estimation of web-based software. We further investigate the estimation accuracy of using genetic algorithm to determine the weight assignment for the proposed models. Preliminary result shows that the linearly and nonlinearly weighted combinational models have better prediction capability than single SRGM and equally weighted combinational model for web-based software.

References

[1]

Bullen, P.S., Mitrinovic, D.S., and Vasic, M., Means and Their Inequalities, Springer, 1988.

Crossref

Google Scholar

[2]

Lyu, M.R., Handbook of Software Reliability Engineering, McGraw-Hill, 1996.

Digital Library

Google Scholar

[3]

Lyu, M.R. and Nikora, A., "Applying Reliability Models More Effectively," IEEE Software, vol. 9, no. 4, pp. 43--52, 1992.

Digital Library

Google Scholar

[4]

Mitchell, M., An Introduction to Genetic Algorithms, The MIT Press, 1998.

Digital Library

Google Scholar

[5]

SourceForge.net, http://sourceforge.net, Last Access Date: 2008 Dec. 11.

Google Scholar

[6]

Tian, J., Rudraraju, S., and Li, Z., "Evaluating Web Software Reliability Based on Workload and Failure Data Extracted from Server Logs," IEEE Transactions on Software Engineering, vol. 30, no. 11, pp. 754--769, 2004.

Digital Library

Google Scholar

[7]

Tsai, W.T., Zhang, D., Chen, Y., Huang, H., Paul, R., and Liao, N., "A Software Reliability Model for Web Services," Proceedings of IASTED International Conference on Software Engineering and Applications, pp. 144--149, MIT Cambridge, USA, 2004.

Google Scholar

Cited By

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Peng KHuang C(2016)Stochastic modelling and simulation approaches to analysing enhanced fault tolerance on service-based software systemsSoftware Testing, Verification & Reliability10.1002/stvr.159626:4(276-293)Online publication date: 1-Jun-2016
https://dl.acm.org/doi/10.1002/stvr.1596
Peng KHuang CWang PHsu CLeung H(2014)Enhanced n-version programming and recovery block techniques for web service systemsProceedings of the International Workshop on Innovative Software Development Methodologies and Practices10.1145/2666581.2666587(11-20)Online publication date: 16-Nov-2014
https://dl.acm.org/doi/10.1145/2666581.2666587
Hsu CHuang C(2014)Optimal Weighted Combinational Models for Software Reliability Estimation and AnalysisIEEE Transactions on Reliability10.1109/TR.2014.231596663:3(731-749)Online publication date: Sep-2014
https://doi.org/10.1109/TR.2014.2315966
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Index Terms

Reliability analysis using weighted combinational models for web-based software
1. General and reference
  1. Cross-computing tools and techniques
    1. Reliability
2. Software and its engineering
  1. Software organization and properties
    1. Extra-functional properties
      1. Software reliability

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Information

Published In

WWW '09: Proceedings of the 18th international conference on World wide web

April 2009

1280 pages

ISBN:9781605584874

DOI:10.1145/1526709

General Chairs:
Juan Quemada
DIT-UPM
,
Gonzalo León
DIT-UPM
,
Program Chairs:
Yoelle Maarek
Google Inc., Israel
,
Wolfgang Nejdl
L3S and Hannover University

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 April 2009

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WWW '09: The 18th International World Wide Web Conference

April 20 - 24, 2009

Madrid, Spain

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Cited By

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Peng KHuang C(2016)Stochastic modelling and simulation approaches to analysing enhanced fault tolerance on service-based software systemsSoftware Testing, Verification & Reliability10.1002/stvr.159626:4(276-293)Online publication date: 1-Jun-2016
https://dl.acm.org/doi/10.1002/stvr.1596
Peng KHuang CWang PHsu CLeung H(2014)Enhanced n-version programming and recovery block techniques for web service systemsProceedings of the International Workshop on Innovative Software Development Methodologies and Practices10.1145/2666581.2666587(11-20)Online publication date: 16-Nov-2014
https://dl.acm.org/doi/10.1145/2666581.2666587
Hsu CHuang C(2014)Optimal Weighted Combinational Models for Software Reliability Estimation and AnalysisIEEE Transactions on Reliability10.1109/TR.2014.231596663:3(731-749)Online publication date: Sep-2014
https://doi.org/10.1109/TR.2014.2315966
Park JSeo YBaik J(2013)A Comparative Analysis of Reliability Assessment Methods for Web-Based SoftwareInternational Journal of Software Innovation10.4018/ijsi.20131001031:4(31-44)Online publication date: 1-Oct-2013
https://doi.org/10.4018/ijsi.2013100103
Park JSeo YBaik J(2013)A Comparative Analysis of Reliability Assessment Methods for Web-based SoftwareInternational Journal of Software Innovation10.4018/ijsi.20130701031:3(34-47)Online publication date: 1-Jul-2013
https://doi.org/10.4018/ijsi.2013070103
Park JKim HBaik J(2013)A Hypothetical Scenario-Based Analysis on Software Reliability Evaluation Approaches in the Web EnvironmentSoftware Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing10.1007/978-3-319-00738-0_10(129-141)Online publication date: 2013
https://doi.org/10.1007/978-3-319-00738-0_10
Huang CLyu M(2011)Estimation and Analysis of Some Generalized Multiple Change-Point Software Reliability ModelsIEEE Transactions on Reliability10.1109/TR.2011.213435060:2(498-514)Online publication date: Jun-2011
https://doi.org/10.1109/TR.2011.2134350
Li HZeng MLu MHu XLi Z(2011)Adaboosting‐based dynamic weighted combination of software reliability growth modelsQuality and Reliability Engineering International10.1002/qre.121628:1(67-84)Online publication date: 31-May-2011
https://doi.org/10.1002/qre.1216

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Discrete software reliability assessment with discretized NHPP models

Neural-network-based approaches for software reliability estimation using dynamic weighted combinational models

A Novel Framework of Software Reliability Evaluation with Software Reliability Growth Models and Software Metrics