A model-based regression test selection approach for embedded applications

  • Authors:
  • Swarnendu Biswas;Rajib Mall;Manoranjan Satpathy;Srihari Sukumaran

  • Affiliations:
  • Department of Computer Science and Engineering, IIT Kharagpur, India;Department of Computer Science and Engineering, IIT Kharagpur, India;GM India Science Lab, Bangalore;GM India Science Lab, Bangalore

  • Venue:
  • ACM SIGSOFT Software Engineering Notes
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

Abstract

Regression test selection techniques for embedded programs have scarcely been reported in the literature. In this paper, we propose a model-based regression test selection technique for embedded programs. Our proposed model, in addition to capturing the data and control dependence aspects, also represents several additional program features that are important for regression test case selection of embedded programs. These features include control flow, exception handling, message paths, task priorities, state information and object relations. We select a regression test suite based on slicing our proposed graph model. We also propose a genetic algorithm-based technique to select an optimal subset of test cases from the set of regression test cases selected after slicing our proposed model.