Pinte FA, Oster N, Saglietti F (2008)
Publication Language: English
Publication Type: Conference contribution, Original article
Publication year: 2008
Publisher: IEEE
Edited Volumes: Proceedings - International Conference on Software Engineering
City/Town: New York, NY, USA
Pages Range: 927-928
Conference Proceedings Title: Companion of the 30th international conference on Software engineering (ICSE Companion '08)
ISBN: 978-1-60558-079-1
URI: http://dl.acm.org/ft_gateway.cfm?id=1370191
This article presents two different tools automating the generation of optimized test data for unit, model-based and integration testing by maximizing the coverage and minimizing the number of test cases required. To cope with these conflicting goals, hybrid self-adaptive and multi-objective evolutionary algorithms were applied. The efficiency was demonstrated by evaluating fault detection capability by mutation testing. Thanks to the effort reduction offered, the approach is particularly suitable for the verification of complex, safety-relevant software systems.
APA:
Pinte, F.-A., Oster, N., & Saglietti, F. (2008). Techniques and Tools for the Automatic Generation of Optimal Test Data at Code, Model and Interface Level. In Companion of the 30th international conference on Software engineering (ICSE Companion '08) (pp. 927-928). Leipzig, DE: New York, NY, USA: IEEE.
MLA:
Pinte, Florin-Avram, Norbert Oster, and Francesca Saglietti. "Techniques and Tools for the Automatic Generation of Optimal Test Data at Code, Model and Interface Level." Proceedings of the 30th International Conference on Software Engineering (ICSE 2008), Leipzig New York, NY, USA: IEEE, 2008. 927-928.
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