Linking software testing results with a machine learning approach

Author:

Rafael Lenz Alexandre,Pozo Aurora,Regina Vergilio Silvia

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference42 articles.

1. Baskiotis, N., Sebag, M., Gaudel, M.-C., Gouraud, S., 2007. A machine learning approach for statistical software testing. In: International Joint Conference on Artificial Intelligence (IJCAI), pp. 2274–2279.

2. Bowring, J., Rehg, J., Harrold, M., 2004. Active learning for automatic classification of software behavior. In: ACM International Symposium on Software Testing and Analysis, pp. 195–205.

3. Briand, L., 2008. Novel applications of machine learning in software testing. In: International Conference on Software Quality, pp. 1–8.

4. Briand, L.C., Labiche, Y., Bawar, Z., 2008. Using machine learning to refine black-box test specifications and test suites. In: International Conference on Software Quality, pp. 135–144.

5. Budd, T.A., 1981. Mutation Analysis: Ideas, Example, Problems and Prospects. Computer Program Testing. North-Holland Publishing Company.

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