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Applying regression test selection for COTS-based applications
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Source International Conference on Software Engineering archive
Proceedings of the 28th international conference on Software engineering table of contents
Shanghai, China
SESSION: Experience papers: software development practices table of contents
Pages: 512 - 522  
Year of Publication: 2006
ISBN:1-59593-375-1
Authors
Jiang Zheng  North Carolina State University, Raleigh, NC
Brian Robinson  ABB Inc.
Laurie Williams  North Carolina State University, Raleigh, NC
Karen Smiley  ABB Inc.
Sponsors
ACM: Association for Computing Machinery
SIGSOFT: ACM Special Interest Group on Software Engineering
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 20,   Downloads (12 Months): 113,   Citation Count: 7
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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.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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CITED BY  7

Collaborative Colleagues:
Jiang Zheng: colleagues
Brian Robinson: colleagues
Laurie Williams: colleagues
Karen Smiley: colleagues