关键词: 软件缺陷预测, 模糊C均值, 模拟退火, 遗传算法, 无监督

Abstract: Software defect prediction is to predict whether there is a bug in a software system module. Traditional researches on software defect prediction mainly focus on supervised method. This type of method needs a lot of instances with labels as the training set. However, in engineering practice, the instances with labels are difficult to obtain. This paper proposes an improved fuzzy C-means algorithm, combining simulated annealing and genetic algorithm, to solve the defect that fuzzy C-means is easily affected by the initial cluster centers. The experimental results show that the proposed method has high robustness and accuracy on software defect prediction.

Key words: software defect prediction, fuzzy C-means, simulated annealing, genetic algorithm, unsupervised