| 基于贝叶斯网络预测克隆代码质量 |
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| 引用本文： | 刘冬瑞,刘东升,张丽萍,侯敏,王春晖. 基于贝叶斯网络预测克隆代码质量[J]. 计算机科学, 2017, 44(4): 165-168 |
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| 作者姓名： | 刘冬瑞 刘东升 张丽萍 侯敏 王春晖 |
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| 作者单位： | 内蒙古师范大学计算机与信息工程学院 呼和浩特010022,内蒙古师范大学计算机与信息工程学院 呼和浩特010022,内蒙古师范大学计算机与信息工程学院 呼和浩特010022,内蒙古师范大学计算机与信息工程学院 呼和浩特010022,内蒙古师范大学计算机与信息工程学院 呼和浩特010022 |
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| 基金项目： | 本文受国家自然科学基金(61363017,61462071),内蒙古自然科学基金资助 |
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| 摘 要： | 针对软件中克隆代码的质量进行研究,评价软件当前所有版本中克隆代码的质量。在此基础上使用贝叶斯网络训练已有样本数据,得到克隆代码质量预测模型,其能预测软件未发布版本中克隆代码的质量,根据评价和预测结果给开发人员提供克隆代码重构和有效复用的建议,防止有害克隆代码的大量繁殖。 实验表明,该方法能够较准确地预测软件中克隆代码的质量。
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| 关 键 词： | 克隆代码 贝叶斯网络 质量评估模型 预测 重构 |
| 收稿时间： | 2015-11-30 |
| 修稿时间： | 2016-02-27 |
Prediction of Code Clone Quality Based on Bayesian Network |
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| LIU Dong-rui,LIU Dong-sheng,ZHANG Li-ping,HOU Min and WANG Chun-hui. Prediction of Code Clone Quality Based on Bayesian Network[J]. Computer Science, 2017, 44(4): 165-168 |
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| Authors: | LIU Dong-rui LIU Dong-sheng ZHANG Li-ping HOU Min WANG Chun-hui |
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| Affiliation: | College of Computer and Information Engineering,Inner Mongolia Normal University,Hohhot 010022,China,College of Computer and Information Engineering,Inner Mongolia Normal University,Hohhot 010022,China,College of Computer and Information Engineering,Inner Mongolia Normal University,Hohhot 010022,China,College of Computer and Information Engineering,Inner Mongolia Normal University,Hohhot 010022,China and College of Computer and Information Engineering,Inner Mongolia Normal University,Hohhot 010022,China |
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| Abstract: | This paper researched on the quality of code clone in the softwareand ,evaluated the code clone quality of the current versions.Then on this basis,Bayesian network was used to train the existing sample data gets the prediction model of code clone which is able to predict the quality.The prediction results are able to help developers make judgments that code clone should be reconstructed or efficiently reused.The experiment shows that the method can be used to predict the quality of code clone in software more accurately. |
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| Keywords: | Code clone Bayesian network Quality evaluation model Prediction Reconstruct |
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