Regression test selection on system requirements

  • Authors:
  • Pavan Kumar Chittimalli;Mary Jean Harrold

  • Affiliations:
  • Tata Consultancy Services Ltd., Atlanta, GA;Georgia Institute of Technology, Atlanta, GA

  • Venue:
  • ISEC '08 Proceedings of the 1st India software engineering conference
  • Year:
  • 2008

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Abstract

Regression testing, which is performed after changes are made to a software system, can be used before release of new versions of the system. However, practitioners often have little time to perform this regression testing because of the quick-release cycles of such modified systems. Thus, they may use a random-testing approach or perform little regression testing. This lack of adequate regression testing can cause bugs in untested parts of the program to be exposed only during production or field usage. To improve the efficiency of the regression testing, and thus enable its use before release, techniques that select and run only those test cases that are related to the changes or prioritize the test cases based on criticality or perceived effectiveness have been presented. These technique typically use some representation of the software such as a system model or the source code to perform the test selection and prioritization. However, in practice, access to a system modelor the source code may not be possible. To provide regression test selection in practice, we have developed, and present in this paper, a novel approach to regression test selection that, instead of using a system model or the source code, uses the system requirements and their associated test cases, which are typically available to developers/testers. The approach uses the set of system requirements, usually in natural language or some informal notation, that represent what is to be tested about the system. The technique uses these requirements, along with the set of test cases and their criticality that are associated with the requirements, to select test cases for use in regression testing. In this paper, we also present a case study that shows the potential effectiveness of our technique