Quantitative analysis for non-linear system performance data using Case-based Reasoning

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)

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Author(s)

Detail(s)

Original languageEnglish
Title of host publicationProceedings - Asia-Pacific Software Engineering Conference, APSEC
Pages346-355
Publication statusPublished - 2010
Externally publishedYes

Publication series

Name
ISSN (Print)1530-1362

Conference

Title17th Asia Pacific Software Engineering Conference: Software for Improving Quality of Life, APSEC 2010
PlaceAustralia
CitySydney, NSW
Period30 November - 3 December 2010

Abstract

Effective software architecture evaluation methods are essential in today's system development for mission critical systems. We have previously developed MEMS and a set of test statistics for evaluating middleware architectures, which proven an effective assessment of important quality attributes and their characterizations. We have observed it is common that many system performance response data are not of linear nature, where using linear modeling is not feasible in these scenarios for system performance predictions. To provide an alternative quantitative assessment on the system performance using actual runtime datasets, we developed a set of non-linear analysis procedure based on Case-based Reasoning (CBR), a machine learning method widely used in another disciplines of Software Engineering. Experiments were carried out based on actual runtime performance datasets. Results confirm that our non-linear analysis method CBR4MEMS produced accurate performance predictions and outperformed linear approaches. Our approach utilizing CBR to enable performance assessments on non-linear datasets, a major step forward to support software architecture evaluation. © 2010 IEEE.

Research Area(s)

  • Case-based Reasoning, Software architecture evaluation, Software measurement

Citation Format(s)

Quantitative analysis for non-linear system performance data using Case-based Reasoning. / Keung, Jacky W.; Nguyen, Thong.

Proceedings - Asia-Pacific Software Engineering Conference, APSEC. 2010. p. 346-355 5693211.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)