A statistical method for middleware system architecture evaluation

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 of the Australian Software Engineering Conference, ASWEC
Pages183-191
Publication statusPublished - 2010
Externally publishedYes

Conference

Title21st Australian Software Engineering Conference, ASWEC 2010
PlaceNew Zealand
CityAuckland
Period6 - 9 April 2010

Abstract

The architecture of complex software systems is a collection of decisions that are very expensive to change. This makes effective software architecture evaluation methods essential in today's system development for mission critical systems. We have previously developed MEMS for evaluating middleware architectures, which provides an effective assessment of important quality attributes and their characterizations. To provide additional quantitative assessments on the overall system performance using actual runtime data, we employed a set of statistical procedures in this work. Our proposed assessment procedures comprises a standard sensitivity analysis procedure that utilizes leverage statistics to identify and remove influential data points, and an estimator for evaluating system stability and a metric for evaluating system load capacity. Experiments were conducted using real runtime datasets. Results show that our procedures effectively identified and isolated abnormal data points, and provided valuable statistics to show system stability. Our approach thus provides a sound statistical basis to support software architecture evaluation. © 2010 IEEE.

Citation Format(s)

A statistical method for middleware system architecture evaluation. / Keung, Jacky W.; Liu, Yan; Foster, Kate; Nguyen, Thong.

Proceedings of the Australian Software Engineering Conference, ASWEC. 2010. p. 183-191 5475039.

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