Attribute reduction based expected outputs generation for statistical software testing

  • Authors:

  • Mao Ye;Boqin Feng;Li Zhu;Yao Lin

  • Affiliations:

  • Department of Computer Science and Technology, Xi'an Jiaotong University, Xi'an, P. R. China;Department of Computer Science and Technology, Xi'an Jiaotong University, Xi'an, P. R. China;School of Software, Xi'an Jiaotong University, Xi'an, P. R. China;Department of Computer Science and Technology, Xi'an Jiaotong University, Xi'an, P. R. China

  • Venue:
  • RSKT'06 Proceedings of the First international conference on Rough Sets and Knowledge Technology
  • Year:
  • 2006

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Abstract

A lot of test cases need to be executed in statistical software testing. A test case consists of a set of inputs and a list of expected outputs. To automatically generate the expected outputs for a lot of test cases is rather difficult. An attribute reduction based approach is proposed in this paper to automatically generate the expected outputs. In this approach the input and output variables of a software are expressed as conditional attributes and decision attributes respectively. The relationship between input and output variables are then obtained by attribute reduction. Thus, the expected outputs for a lot of test sets are automatically generated via the relationship. Finally, a case study and the comparison results are presented, which show that the method is effective