Abstract
The fuzzy measure and fuzzy integral are applied to the classification of software defects in this paper. The fuzzy measure of software attributes and attributes’ sets are treated by genetic algorithm, and then software attributes are fused by the Choquet fuzzy integral algorithm. Finally, the class labels of software modules can be output. Experimental results have shown that there are interactions between characteristic attributes of software modules, and also proved that the fuzzy integral fusing method using Fuzzy Measure based on Genetic Algorithm (GA-FM) can significantly improve the accuracy for software defect prediction.
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Foundation item: Supported by the Natural Science Foundation of Shandong Province (ZR2013FL034)
Biography: LI Kewen, male, Ph.D., Associate professor, research direction: computational intelligence, software engineering, big data.
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Li, K., Chen, C., Liu, W. et al. Software defect prediction using fuzzy integral fusion based on GA-FM. Wuhan Univ. J. Nat. Sci. 19, 405–408 (2014). https://doi.org/10.1007/s11859-014-1032-2
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DOI: https://doi.org/10.1007/s11859-014-1032-2