Test-data generation guided by static defect detection

  • Authors:

  • Dan Hao;Lu Zhang;Ming-Hao Liu;He Li;Jia-Su Sun

  • Affiliations:

  • Key Laboratory of High Confidence Software Technologies, Ministry of Education, Beijing, China and Institute of Software, School of Electronics Engineering and Computer Science, Peking University, ...;Key Laboratory of High Confidence Software Technologies, Ministry of Education, Beijing, China and Institute of Software, School of Electronics Engineering and Computer Science, Peking University, ...;Key Laboratory of High Confidence Software Technologies, Ministry of Education, Beijing, China and Institute of Software, School of Electronics Engineering and Computer Science, Peking University, ...;Key Laboratory of High Confidence Software Technologies, Ministry of Education, Beijing, China and Institute of Software, School of Electronics Engineering and Computer Science, Peking University, ...;Key Laboratory of High Confidence Software Technologies, Ministry of Education, Beijing, China and Institute of Software, School of Electronics Engineering and Computer Science, Peking University, ...

  • Venue:
  • Journal of Computer Science and Technology
  • Year:
  • 2009

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Abstract

Software testing is an important technique to assure the quality of software systems, especially high-confidence systems. To automate the process of software testing, many automatic test-data generation techniques have been proposed. To generate effective test data, we propose a test-data generation technique guided by static defect detection in this paper. Using static defect detection analysis, our approach first identifies a set of suspicious statements which are likely to contain faults, then generates test data to cover these suspicious statements by converting the problem of test-data generation to the constraint satisfaction problem. We performed a case study to validate the effectiveness of our approach, and made a simple comparison with another test-data generation on-line tool, JUnit Factory. The results show that, compared with JUnit Factory, our approach generates fewer test data that are competitive on fault detection.