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ABSTRACT
ABB incorporates a variety of commercial-off-the-shelf (COTS) components in its products. When new releases of these components are made available for integration and testing, source code is often not provided. Various regression test selection processes have been developed and have been shown to be cost effectiveness. However, the majority of these test selection techniques rely on access to source code for change identification. In this paper we present the application of the lightweight Integrated - Black-box Approach for Component Change Identification (I-BACCI) Version 3 process that select regression tests for applications that use COTS components. Two case studies, examining a total of nine new component releases, were conducted at ABB on products written in C/C++ to determine the effectiveness of I-BACCI. The results of the case studies indicate this process can reduce the required number of regression tests at least 70% without sacrificing the regression fault exposure.
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Sheng Huang , Yang Chen , Jun Zhu , Zhong Jie Li , Hua Fang Tan, An optimized change-driven regression testing selection strategy for binary Java applications, Proceedings of the 2009 ACM symposium on Applied Computing, March 08-12, 2009, Honolulu, Hawaii
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