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21st IEEE International Conference on Automated Software Engineering (ASE'06)   pp. 59-68
An Empirical Comparison of Automated Generation and Classification Techniques for Object-Oriented Unit Testing
Marcelo d’Amorim, University of Illinois, Urbana-Champaign, IL, USA
Carlos Pacheco, MIT, Cambridge, MA, USA
Tao Xie, North Carolina State University, Raleigh, NC, USA
Darko Marinov, University of Illinois, Urbana-Champaign, IL, USA
Michael D. Ernst, MIT, Cambridge, MA, USA

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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ASE.2006.13
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Abstract
Testing involves two major activities: generating test inputs and determining whether they reveal faults. Automated test generation techniques include random generation and symbolic execution. Automated test classification techniques include ones based on uncaught exceptions and violations of operational models inferred from manually provided tests. Previous research on unit testing for object-oriented programs developed three pairs of these techniques: model-based random testing, exception-based random testing, and exception-based symbolic testing. We develop a novel pair, model-based symbolic testing. We also empirically compare all four pairs of these generation and classification techniques. The results show that the pairs are complementary (i.e., reveal faults differently), with their respective strengths and weaknesses.
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Citation:  Marcelo d’Amorim, Carlos Pacheco, Tao Xie, Darko Marinov, Michael D. Ernst, "An Empirical Comparison of Automated Generation and Classification Techniques for Object-Oriented Unit Testing," ase, pp. 59-68,  21st IEEE International Conference on Automated Software Engineering (ASE'06),  2006