An adaptive bayesian approach for URL selection to test performance of large scale web-based systems

Gias, A.U. and Sakib, K. 2014. An adaptive bayesian approach for URL selection to test performance of large scale web-based systems. 36th International Conference on Software Engineering. Hyderabad, India 31 May - 07 Jun 2014 IEEE . https://doi.org/10.1145/2591062.2591139

TitleAn adaptive bayesian approach for URL selection to test performance of large scale web-based systems
AuthorsGias, A.U. and Sakib, K.
TypeConference paper
Abstract

In case of large scale web-based systems, scripts for performance testing are updated iteratively. In each script, multiple URLs of the system are considered depending on intuitions that those URLs will expose the performance bugs. This paper proposes a Bayesian approach for including a URL to a test script based on its probability of being time intensive. As the testing goes on the scheme adaptively updates its knowledge regarding a URL. The comparison with existing methods shows that the proposed technique performs similar in guiding applications towards intensive tasks, which helps to expose performance bugs.

Year2014
Conference36th International Conference on Software Engineering
PublisherIEEE
Publication dates
Published2014
ISBN9781450327688
Digital Object Identifier (DOI)https://doi.org/10.1145/2591062.2591139
Web address (URL)http://www.scopus.com/inward/record.url?eid=2-s2.0-84903649664&partnerID=MN8TOARS

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