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引用次数: 6

摘要

计算机科学需要计算不同计算机程序相似度的标准方法。这种度量在许多不同的领域都很有用,比如克隆检测、重构、编译器优化和运行时优化。这些标准对于发现剽窃、商业秘密盗窃、版权侵权和专利侵权尤其重要。其他用途包括在专有程序中定位开源代码和确定不同程序的作者。在之前的一篇论文(R. Zeidman, 2006)中,我介绍了源代码相关性的概念,提出了这种度量的理论基础,并描述了一个比较软件源代码和计算相关性的程序CodeMatchreg。本文将所描述的源代码关联方法与现有的源代码比较方法进行了比较,发现其具有明显的优越性。本文对源代码相关的定义进行了改进,提出了一个新的、更健壮的多维源代码相关的定义。
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Multidimensional Correlation of Software Source Code
Standard ways of calculating the similarity of different computer programs are needed in computer science. Such measurements can be useful in many different areas such as clone detection, refactoring, compiler optimization, and run-time optimization. Such standards are particularly important for uncovering plagiarism, trade secret theft, copyright infringement, and patent infringement. Other uses include locating open source code within a proprietary program and determining the authors of different programs. In a previous paper (R. Zeidman, 2006) I introduced the concept of source code correlation, presented a theoretical basis for such a measure, and described a program, CodeMatchreg, that compares software source code and calculates correlation. That paper compared the described method of source code correlation against existing methods of comparing source code and found it to be significantly superior. This paper refines that definition of source code correlation and presents a new, more robust, definition of multidimensional source code correlation.
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