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Automatic, load-independent detection of performance regressions by transaction profiles

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conference contribution
posted on 2013-11-28, 15:33 authored by Shadi Ghaith, Miao Wang, Philip Perry, John Murphy
Performance regression testing is an important step in the production process of enterprise applications. Yet, analysing this type of testing data is mainly conducted manually and depends on the load applied during the test. To ease such a manual task we present an automated, load-independent technique to detect performance regression anomalies based on the analysis of performance testing data using a con- cept known as Transaction Pro le. The approach can be automated and it utilises data already available to the per- formance testing along with the queueing network model of the testing system. The presented \Transaction Pro le Run Report"was able to automatically catch performance regression anomalies ca- used by software changes and isolate them from those caused by load variations with a precision of 80% in a case study conducted against an open source application. Hence, by deploying our system, the testing teams are able to detect performance regression anomalies by avoiding the manual approach and eliminating the need to do extra runs with varying load.

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Publication

International Symposium in Software Testing and Analysis (ISSTA 13) Joining AcadeMiA and Industry Contributions to testing Automation (JAMAICA);pp. 59-64

Publisher

Association for Computing Machinery

Note

peer-reviewed

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SFI

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"© ACM, 2013. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in International Symposium in Software Testing and Analysis (ISSTA 13) Joining AcadeMiA and Industry Contributions to testing Automation (JAMAICA), pp. 59-64 http://dx.doi.org/10.1145/2489280.2489286

Language

English

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