Software Defect Prediction Using Fuzzy Integral and Genetic Algorithm

The fuzzy classification plays an important role to predict defect of software modules. In this paper, the fuzzy measure (FM) is used to improve the predict accuracy and capability by acquiring all possible interactions among metrics and apply Choquet integral (CI) for classifying in n dimensional space and automatic searching the least misclassification rate based on distance. To implement the model, we also need to determine the unknown parameters, and which is implemented using genetic algorithm (GA) on the training data. The proposed model is tested on the four NASA software projects. The results indicate that the predict performance of proposed model is better than other predict models.