基于双重维度发现代码变更模式的挖掘方法
在代码演变的历史中，识别出重复的代码变更，对工具开发者、项目开发者、代码研究者都大有裨益。本文在代码演变的历史信息中，通过抽取细粒度的变更，采用两重维度划分事务，应用频繁项集挖掘算法，提取出一些频繁的代码变更模式。并以真实项目为对象进行了实验分析，结果表明该方法能有效挖掘出项目演变历史中的频繁代码变更，检测出有意义的高层次程序转换。...
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| Published in | 计算机应用研究 Vol. 34; no. 8; pp. 2252 - 2257 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
武汉大学 计算机学院 软件工程国家重点实验室,武汉,430072
2017
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1001-3695 |
| DOI | 10.3969/j.issn.1001-3695.2017.08.003 |
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| Abstract | 在代码演变的历史中，识别出重复的代码变更，对工具开发者、项目开发者、代码研究者都大有裨益。本文在代码演变的历史信息中，通过抽取细粒度的变更，采用两重维度划分事务，应用频繁项集挖掘算法，提取出一些频繁的代码变更模式。并以真实项目为对象进行了实验分析，结果表明该方法能有效挖掘出项目演变历史中的频繁代码变更，检测出有意义的高层次程序转换。 |
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| AbstractList | 在代码演变的历史中，识别出重复的代码变更，对工具开发者、项目开发者、代码研究者都大有裨益。本文在代码演变的历史信息中，通过抽取细粒度的变更，采用两重维度划分事务，应用频繁项集挖掘算法，提取出一些频繁的代码变更模式。并以真实项目为对象进行了实验分析，结果表明该方法能有效挖掘出项目演变历史中的频繁代码变更，检测出有意义的高层次程序转换。 TP311.52; 在代码演变的历史中,识别出重复的代码变更,对工具开发者、项目开发者、代码研究者都大有裨益.在代码演变的历史信息中,通过抽取细粒度的变更,采用两重维度划分事务,应用频繁项集挖掘算法提取出一些频繁的代码变更模式.以真实项目为对象进行了实验分析,结果表明该方法能有效挖掘出项目演变历史中的频繁代码变更,检测出有意义的高层次程序转换. |
| Abstract_FL | Identifying repetitive code changes from the history of code evolution, can benefit tool builders, program developers and code researchers.This paper employed the algorithm of change distiller to extract fine-grained changes from the code evolution history and then derived transactions using both the temporal and spacial dimentions.This paper designed a frequent multiple instance itemset mining algorithm, and applied to derive valuable high-level program change patterns.Experiment results on the real software projects illustrate that this approach can find the frequent code changes from the history of program evolution, reveal significant and high-level program transformations. |
| Author | 左翔宇 刘婧 何璐璐 |
| AuthorAffiliation | 武汉大学计算机学院软件工程国家重点实验室,武汉430072 |
| AuthorAffiliation_xml | – name: 武汉大学 计算机学院 软件工程国家重点实验室,武汉,430072 |
| Author_FL | Liu Jing He Lulu Zuo Xiangyu |
| Author_FL_xml | – sequence: 1 fullname: Zuo Xiangyu – sequence: 2 fullname: Liu Jing – sequence: 3 fullname: He Lulu |
| Author_xml | – sequence: 1 fullname: 左翔宇 刘婧 何璐璐 |
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| DocumentTitleAlternate | Software change pattern mining based on double dimensions |
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| Keywords | both temporal and spacial dimensions 高层次程序转换 代码变更模式 两重维度 history of code evolution 频繁项集挖掘 code change pattern 代码演变历史 frequent itemset mining high-level program transformation |
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| Notes | 51-1196/TP history of code evolution; code change pattern; both temporal and spatial dimensions; frequent itemset min- ing; high-level program transformation Identifying repetitive code changes from the history of code evolution, can benefit tool builders, program developers and code researchers. This paper employed the algorithm of change distiller to extract fine-grained changes from the code evo- lution history and then derived transactions using both the temporal and spaeial dimentions. This paper designed a frequent multiple instance itemset mining algorithm, and applied to derive valuable high-level program change patterns. Experiment re- suits on the real software projects illustrate that this approach can find the frequent code changes from the history of program evolution, reveal significant and high-level program transformations. Zuo Xiangyu, Liu Jing, He Lulu （ State Key Laboratory of Software Engineering, School of Computer, Wuhan University, Wuhan 430072, China） |
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| SubjectTerms | 两重维度 代码变更模式 代码演变历史 频繁项集挖掘 高层次程序转换 |
| Title | 基于双重维度发现代码变更模式的挖掘方法 |
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