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Huang, L., Jia, J., Yu, B., Chun, B.-G., Maniatis, P. and Naik, M. (2010) Predicting Execution Time of Computer Programs Using Sparse Polynomial Regression. Proceedings of the 23rd International Conference on Neural Information Processing Systems, Vol. 1, Vancouver, 6-9 December 2010, 883-891.

has been cited by the following article:

• TITLE: A Study of Performance Testing in Configurable Software Systems

  AUTHORS: Xue Han

  KEYWORDS: Configurable Software Systems, Performance Testing, Software Configuration, Performance Bug Study

  JOURNAL NAME: Journal of Software Engineering and Applications, Vol.14 No.9, September 13, 2021

  ABSTRACT: Customizing applications through program configuration options has been proved by many open-source and commercial projects as one of the best practices in software engineering. However, traditional performance testing is not in synch with this industrial practice. Traditional performance testing techniques consider program inputs as the only external factor. It ignores the performance influence of configuration options. This study aims to stimulate research interest in performance testing in the context of configurable software systems by answering three research questions. That is, why it is necessary to conduct research in performance testing, what are the state-of-the-art techniques, and how do we conduct performance testing research in configurable software systems. In this study, we examine the unique characteristics and challenges of performance testing research in configurable software systems. We review and discuss research topics on the performance bug study, performance anti-patterns, program analysis, and performance testing. We share the research findings from the empirical study and outline the opening opportunities for new and advanced researchers to contribute to the research community.