Although there are quite a few approaches to Coverage Directed test Generation aided by Machine Learning which have been applied successfully to small and medium size digital designs, it is not clear how they would scale on more elaborate industrial-level designs. This paper evaluates one of these techniques, called MicroGP, on a fully fledged industrial design. The results indicate relative success evidenced by a good level of code coverage achieved with reasonably compact tests when compared to traditional test generation approaches. However, there is scope for improvement especially with respect to the diversity of the tests evolved. © 2011 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Ioannides, C., Barrett, G., & Eder, K. (2011). Feedback-based coverage directed test generation: An industrial evaluation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6504 LNCS, pp. 112–128). https://doi.org/10.1007/978-3-642-19583-9_13
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