Predicting inconsistent change probability of code clone based on latent Dirichlet allocation model

doi:10.11772/j.issn.1001-9081.2014.06.1788

Journal of Computer Applications ›› 2014, Vol. 34 ›› Issue (6): 1788-1791.DOI: 10.11772/j.issn.1001-9081.2014.06.1788

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Predicting inconsistent change probability of code clone based on latent Dirichlet allocation model

YI Lili,ZHANG Liping,WANG Chunhui,TU Ying,LIU Dongsheng

College of Computer and Information Engineering, Inner Mongolia Normal University, Hohhot Nei Mongol 010022, China

Received:2013-11-07 Revised:2014-01-17 Online:2014-07-02 Published:2014-06-01
Contact: LIU Dongsheng
Supported by:
National Natural Science Foundation

基于潜在狄利克雷分配模型预测克隆代码不一致变化的可能

尹丽丽,张丽萍,王春辉,涂颖,刘东升

内蒙古师范大学计算机与信息工程学院,呼和浩特 010022

通讯作者: 刘东升
作者简介:尹丽丽(1987-), 女,内蒙古赤峰人,硕士研究生,主要研究方向:代码分析;张丽萍(1974-), 女,内蒙古呼和浩特人,副教授,主要研究方向:软件工程、代码分析;王春晖(1979-),女,内蒙古呼和浩特人,讲师,硕士,主要研究方向:软件工程、代码分析;刘东升(1956-),男,内蒙古呼和浩特人,教授,主要研究方向:软件工程、代码分析。
基金资助:
重庆市科委基础与前沿研究项目

Abstract

Abstract:

The activities of the programmers including copy, paste and modify result in a lot of code clone in the software systems. However, the inconsistent change of code clone is the main reason that causes program error and increases maintenance costs in the evolutionary process of the software version. To solve this problem, a new research method was proposed. The mapping relationship between the clone groups was built at first. Then the theme of lineal cloning cluster was extracted using Latent Dirichlet Allocation (LDA) model. Finally, the inconsistent change probability of code clone was predicted. A software which contains eight versions was tested and an obvious discrimination was got. The experimental results show that the method can effectively predict the probability of inconsistent change and be used for evaluating quality and credibility of software.

摘要：

程序员对源代码的拷贝、粘贴及修改活动会导致软件中出现大量的克隆代码,而在版本的进化过程中,克隆代码的不一致变化是引起程序错误的主要原因,同时会增加维护成本。为了解决该问题,提出一种新的研究方法:首先构建版本间克隆群的映射关系,其次借助潜在狄利克雷分配(LDA)模型提取直系克隆群集主题,最后预测克隆代码不一致变化的可能性。对一款软件的8个版本进行了实验,实验结果的区分度明显,可以有效地预测不一致变化的可能性，评估软件质量和可信性。

CLC Number:

TP311

YI Lili ZHANG Liping WANG Chunhui TU Ying LIU Dongsheng. Predicting inconsistent change probability of code clone based on latent Dirichlet allocation model[J]. Journal of Computer Applications, 2014, 34(6): 1788-1791.

尹丽丽张丽萍王春辉涂颖刘东升. 基于潜在狄利克雷分配模型预测克隆代码不一致变化的可能[J]. 计算机应用, 2014, 34(6): 1788-1791.

References

[1]KAPSER C, GODFREY M W. "Cloning considered harmful" considered harmful[C]// WCRE 2006: Proceedings of the 13th Working Conference on Reverse Engineering. Piscataway: IEEE Press, 2006: 19-28.
[2]KOSCHKE R. Survey of research on software clones[EB/OL].[2013-10-10]. http://drops.dagstuhl.de/volltexte/2007/962/pdf/06301.KoschkeRainer.962.pdf.
[3]ROY C K, CORDY J R. A survey on software clone detection research, 541[R]. Kingston: Queen's University, 2007.
[4]JUERGENS E, DEISSENBOECK F, HUMMEL B, et al. Do code clones matter?[C]// Proceedings of the 31st International Conference on Software Engineering. Washington, DC: IEEE Computer Society, 2009: 485-495.
[5]AVERSANO L, CERULO L, PENTA M D. How clones are maintained: an empirical study[C]// Proceedings of the 11th European Conference on Software Maintenance and Reengineering. Piscataway: IEEE Press, 2007: 81-90.
[6]THUMMALAPENTA S, CERULO L, AVERSANO L, et al. An empirical study on the maintenance of source code clones[J]. Empirical Software Engineering, 2009, 15(1): 1-34.
[7]GDE N, KOSCHKE R. Frequency and risks of changes to clones[C]// Proceedings of the 33rd International Conference on Software Engineering. New York: ACM press, 2011: 311-320.
[8]JIN J, LI M, HUA Z, et al. Code function recognition approach based on LDA and static analysis[EB/OL]. [2012-01-05].http://www.cnki.net/kcms/detail/11.2127.TP.20121130.1126.007.html.(金靖,李萌,华哲邦,等.一种基于LDA和静态分析的代码功能识别方法[EB/OL]. [2012-01-05]. http://www.cnki.net/kcms/detail/11.2127.TP.20121130.1126.007.html.).
[9]THOMAS S W, ADAMS B, HASSAN A E, et al. Studying software evolution using topic models[J]. Science of Computer Programming, 2012, 80(B): 1-23.
[10]THOMAS S W, ADAMS B, HASSAN A E, et al. modeling the evolution of topics in source code histories[C]// Proceedings of the 8th Working Conference on Mining Software Repositories. New York: ACM Press, 2011: 173-182.
[11]THOMAS S W, ADAMS B, HASSAN A E, et al. Validating the use of topic models for software evolution[C]// Proceedings of the 2010 10th IEEE Working Conference on Source Code Analysis and Manipulation. Piscataway: IEEE Press, 2010: 55-64.
[12]NGUYEN A T, NGUYEN T T, AL-KOFAHI J, et al. A topic-based approach for narrowing the search space of buggy files from a bug report[C]// Proceedings of the 2011 26th IEEE/ACM International Conference on Automated Software Engineering. Piscataway: IEEE Press, 2011: 263-272.
[13]MASKERI G, SARKAR S, HEAFIELD K. Mining business topics in source code using latent Dirichlet allocation[C]// Proceedings of the 1st India Software Engineering Conference. New York: ACM Press, 2008: 113-120.
[14]SHI Q, ZHANG L, MENG F, et al. A novel detection approach for statement clones[C]// Proceedings of the 2013 4th IEEE International Conference on Software Engineering and Service Science. Piscataway: IEEE Press, 2013: 27-30.
[15]SAHHA R K, ASADUZZAMAN M, ZIBRAN M F, et al. Evaluating code clone genealogies at release level: an empirical study[C]// Proceedings of the 2010 10th IEEE Working Conference on Source Code Analysis and Manipulation. Piscataway: IEEE Press, 2010: 87-96.
[16]LIU Y, POSHYVANYK D, FERENC R, et al. Modeling class cohesion as mixtures of latent topics[C]// ICSM 2009: Proceedings of the 2009 IEEE International Conference on Software Maintenance. Piscataway: IEEE Press, 2009: 233-242.

Predicting inconsistent change probability of code clone based on latent Dirichlet allocation model

基于潜在狄利克雷分配模型预测克隆代码不一致变化的可能

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