Novel Insights on Cross Project Fault Prediction Applied to Automotive Software-Reference-Cited by-同舟云学术

Novel Insights on Cross Project Fault Prediction Applied to Automotive Software

Published:2015 Issue: Volume: Page:141-157
ISSN:0302-9743
Container-title:Testing Software and Systems
language:
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Author:

Altinger Harald,Herbold Steffen,Grabowski Jens,Wotawa Franz

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-25945-1_9

Reference29 articles.

1. Altinger, H., Siegl, S., Dajsuren, Y., Wotawa, F.: A novel industry grade dataset for fault prediction based on model-driven developed automotive embedded software. In: Proceedings of the 12th Working Conference on Mining Software Repositories (MSR). IEEE, Florence, Italy (2015)

2. Altinger, H., Wotawa, F., Schurius, M.: Testing methods used in the automotive industry: results from a survey. In: Proceedings of the 2014 Workshop on Joining AcadeMiA and Industry Contributions to Test Automation and Model-Based Testing (JAMAICA). ACM (2014)

3. Bell, R.M., Ostrand, T.J., Weyuker, E.J.: Looking for bugs in all the right places. In: Proceedings of the 2006 International Symposium on Software Testing and Analysis (ISSTA). ACM (2006)

4. Broy, M.: Challenges in automotive software engineering. In: Proceedings of the 28th International Conference on Software Engineering. ACM (2006). http://doi.acm.org/10.1145/1134285.1134292

5. Camargo Cruz, A.E., Ochimizu, K.: Towards logistic regression models for predicting fault-prone code across software projects. In: Proceedings of the 3rd International Symposium on Empirical Software Engineering and Measurement (ESEM). IEEE Computer Society (2009)

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