In regression testing selection when source code is not available
Proceedings of the 20th IEEE/ACM international Conference on Automated software engineering
Applying regression test selection for COTS-based applications
Proceedings of the 28th international conference on Software engineering
Regression Test Selection for Black-box Dynamic Link Library Components
IWICSS '07 Proceedings of the Second International Workshop on Incorporating COTS Software into Software Systems: Tools and Techniques
Pallino: automation to support regression test selection for cots-based applications
Proceedings of the twenty-second IEEE/ACM international conference on Automated software engineering
Extended firewall for regression testing: an experience report
Journal of Software Maintenance and Evolution: Research and Practice
A systematic review on regression test selection techniques
Information and Software Technology
A qualitative survey of regression testing practices
PROFES'10 Proceedings of the 11th international conference on Product-Focused Software Process Improvement
Regression testing minimization, selection and prioritization: a survey
Software Testing, Verification & Reliability
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Industrial real-time systems are complex and need to be thoroughly tested before being released to the customer. We have found that last minute changes are often responsible for the introduction of defects, causing serious problems for the customer. In this paper, we will demonstrate that these defects can be introduced into real-time software in diverse ways, and there is no simple regression testing method that can deal with all of these defect sources. This paper will describe the application of a testing firewall for regression testing whose form will differ depending upon the defect. The idea of the testing firewall is to limit the regression testing to those potentially affected system elements directly dependent upon changed system elements, and then to thoroughly test these elements. This has resulted in substantial savings in regression testing costs, and yet has been effective in detecting critical defects with significant implication in terms of customer acceptance at ABB. Empirical studies will be reported for these experiences in an industrial setting.