一种基于模糊形式概念分析的程序聚类方法.pdfVIP

* 一种基于模糊形式概念分析的程序聚类方法 许佳卿 彭鑫 赵文耘 (复旦大学计算机科学技术学院 上海 200433) Program Clustering for Comprehension based on Fuzzy Formal Concept Analysis Xu Jiaqing, Peng Xin and Zhao Wenyun (School of Computer Science, Fudan University, Shanghai 200433) Abstract Program clustering can help program comprehension and architecture analysis by clustering program units relevant to certain requirement or design element. Formal concept analysis (FCA) has been widely adopted in text-analysis-based program clustering. However, existing FCA-based methods are based on one-valued attributes (with or without), and cannot deal with the fuzzy information in program clustering. In this paper, a text-analysis-based program clustering method using fuzzy FCA is proposed. The method includes a process of fuzzy attribute computation and a construction algorithm for fuzzy concept lattice, which can ensure a complete and non-redundant lattice. A semi-automatic analysis tool has been developed for the method and applied in a case study of a commercial bookstore management system. Results of the experiment show that the method can help to obtain clusters with sound fuzzy features for program comprehension, which are also recognized by former developers of the system. Key words Formal Concept Analysis; fuzzy FCA; fuzzy attribute; program clustering; program comprehension 摘要 程序聚类通过将与同一个需求或设计元素相关的代码单元聚集在一起来辅助程序理 解及系统结构分析。其中，形式概念分析（FCA ）是一类被广泛采用的程序聚类技术。然 而现有基于 FCA 的程序聚类方法都是基于二值属性构建的，无法处理模糊信息。本文提出 将模糊概念分析用于基于文本分析的程序聚类，提出了一种支持模糊信息的程序聚类方法。 该方法包括模糊属性的采集过程以及相应的模糊概念格的构造算法。在此基础上，我们开 发了一个半自动化的程序分析工具，并将其应用到一个商业软件分析中。初步的实验结果 表明该方法能够有效地支持基于模糊特征的程序聚类，对于提高遗留系统的维护效率有明 显的帮助。