Automated Test Data Generation for Coverage: Haven’t We Solved This Problem Yet?

by Kiran Lakhotia, Phil McMinn and Mark Harman

Testing: Academic and Industrial Conference — Practice And Research Techniques (TAIC PART 2009)



Whilst there is much evidence that both concolic and search based testing can outperform random testing, there has been little work demonstrating the effectiveness of either technique with complete real world software applications. As a consequence, many researchers have doubts not only about the scalability of both approaches but also their applicability to production code. This paper performs an empirical study applying a concolic tool, CUTE, and a search based tool, AUSTIN, to the source code of four large open source applications. Each tool is applied ‘out of the box’; that is without writing additional code for special handling of ... [more]


Reference

Kiran Lakhotia, Phil McMinn and Mark Harman. Automated Test Data Generation for Coverage: Haven’t We Solved This Problem Yet?Testing: Academic and Industrial Conference — Practice And Research Techniques (TAIC PART 2009), pp. 95–104, 2009


Bibtex Entry
@inproceedings{Lakhotia2009,
  author    = "Lakhotia, Kiran and McMinn, Phil and Harman, Mark",
  title     = "Automated Test Data Generation for Coverage: Haven't We Solved This Problem Yet?",
  booktitle = "Testing: Academic and Industrial Conference --- Practice And Research Techniques (TAIC PART 2009)",
  pages     = "95--104",
  year      = "2009",
  publisher = "IEEE"
}