Predicting the Cost-Effectiveness of Regression Testing Strategies

Abstract

Selective regression testing strategies aim at choosing an appropriate subset of test cases from among a previously run test suite for a software system, based on information about the changes made to the system to create new versions. Although there has been a significant amount of research in recent years on the design of such strategies, there has been significantly less investigation of their cost-effectiveness. In this paper some computationally efficient predictors of the cost-effectiveness of the two main classes of selective regression testing approaches are presented. A case study is described in which these predictors are used to assess the appropriateness of using a particular regression testing strategy to test multiple versions of a widely-used software system.

BibTeX

@inproceedings{Rosenblum-Weyuker:FSE96,
  author    = {David S. Rosenblum and
               Elaine J. Weyuker},
  title     = {Predicting the {Cost-Effectiveness} of Regression Testing Strategies},
  booktitle = {FSE},
  pages     = {118--126},
  publisher = {{ACM}},
  year      = {1996},
}

Predicting the Cost-Effectiveness of Regression Testing Strategies

Abstract

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