基于DA-SVM的软件缺陷预测模型

doi:10.3969/j.issn.10062475.2017.02.007

计算机与现代化

基于DA-SVM的软件缺陷预测模型

(南京航空航天大学计算机科学与技术学院,江苏南京210016)

收稿日期:2016-06-08 出版日期:2017-03-09 发布日期:2017-03-20
作者简介:甘露（1991-），女，安徽宁国人，南京航空航天大学计算机科学与技术学院硕士研究生，研究方向：软件测试；臧洌（1964-），女，副教授，硕士，研究方向：网络安全及软件可靠性；李航（1992-），男，硕士研究生，研究方向：机器学习。

Software Defect Prediction Model Based on DA-SVM

(College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

Received:2016-06-08 Online:2017-03-09 Published:2017-03-20

摘要/Abstract

摘要：

特征提取是软件缺陷预测技术研究中的重要环节，而现有的特征提取方法无法准确获得特征之间的非线性依赖关系，因而无法提高软件缺陷预测的准确性。针对该问题，本文构建基于降噪编码器和支持向量机的软件缺陷预测模型(Denoising Autoencoder Support Vector Machine，DA-SVM)。首先利用降噪编码器进行特征提取，然后将提取的特征作为支持向量机的输入向量,最后再进行软件缺陷预测。实验结果表明，DASVM提高了软件缺陷预测的准确度，同时降低了历史数据中的噪声，增强了软件预测模型的鲁棒性。
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关键词: 特征提取, 软件缺陷预测, 降噪自动编码器, 支持向量机

Abstract:

Feature extraction is an important step in software defect prediction technology research. However, the existing feature extraction cannot accurately obtain the nonlinear dependence relations among features, thus these methods are unable to improve the accuracy of software defect prediction model. In this paper, to solve this question we propose a software defect prediction model (Denoising Autoencoder Support Vector Machine, DA-SVM) which is based on denoising autoencoder and Support Vector Machine. Firstly, the model extracts features by using denoising autoencoder, secondly uses these features as input of support vector machine, lastly, uses this model to predict bugs. Experimental results show that DA-SVM not only improves the accuracy of software defect prediction model, but also reduces the noise of history data and enhances the robustness of the software defect prediction model.
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Key words: feature extraction, software defect prediction, denoising autoencoder, support vector machine

中图分类号:

TP311

甘露，臧洌，李航. 基于DA-SVM的软件缺陷预测模型[J]. 计算机与现代化, doi: 10.3969/j.issn.10062475.2017.02.007.

GAN Lu, ZANG Lie, LI Hang. Software Defect Prediction Model Based on DA-SVM[J]. Computer and Modernization, doi: 10.3969/j.issn.10062475.2017.02.007.

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基于DA-SVM的软件缺陷预测模型

Software Defect Prediction Model Based on DA-SVM

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