形式概念分析与信息检索相结合的源代码概念定位方法

D. Poshyvanyk, Andrian Marcus
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引用次数: 262

摘要

本文提出了一种结合形式概念分析(FCA)和潜在语义索引(LSI)的方法来解决源代码中的概念定位问题。在提出的方法中,LSI用于将程序员编写的查询中表达的概念映射到源代码的相关部分,以搜索结果的排序列表的形式呈现。给定源代码元素的排序列表,我们的方法从这些文档中选择最相关的属性,并将结果组织在通过FCA生成的概念格中。在一个案例研究方法是评估的概念在eclipse的源代码位置,一个工业规模集成开发环境。实例研究结果表明,该方法可以有效地组织搜索结果子集中存在的不同概念及其关系。提出的概念定位方法优于简单的搜索结果排序,减少了程序员的工作量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Combining Formal Concept Analysis with Information Retrieval for Concept Location in Source Code
The paper addresses the problem of concept location in source code by presenting an approach which combines formal concept analysis (FCA) and latent semantic indexing (LSI). In the proposed approach, LSI is used to map the concepts expressed in queries written by the programmer to relevant parts of the source code, presented as a ranked list of search results. Given the ranked list of source code elements, our approach selects most relevant attributes from these documents and organizes the results in a concept lattice, generated via FCA. The approach is evaluated in a case study on concept location in the source code of eclipse, an industrial size integrated development environment. The results of the case study show that the proposed approach is effective in organizing different concepts and their relationships present in the subset of the search results. The proposed concept location method outperforms the simple ranking of the search results, reducing the programmers' effort.
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