Multilingual coprus of program and its document-from the viewpoint of "Software = program + document"-

程序及其文档的多语言库——从“软件=程序文档”的角度来看——

基本信息

批准号：
16200001
负责人：
INAGAKI Yasuyoshi
金额：
$ 30.12万
依托单位：
Aichi Prefectural University
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (A)
财政年份：
2004
资助国家：
日本
起止时间：
2004 至 2006
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-16200001/
关键词：
compound word division correspondence of identifiers comment sentence software repository CASE tool platform dependency structure corpus searching identifier naming assist 情報抽出 Support Vector Machine 差分抽出用例検索クエリ自動生成翻訳文の対応付け

项目摘要

We aim the CASE tool that handles not only source program written in artificial language but also document described in natural language. The results of our research are as follows:1. We developed the model of comments in source program, as an extension of our fine grained model of C language.2. We proposed a method to take correspondence between source program and document, by using identifiers which appear in both. Our method distinguishes "definition" and "reference" by considering context.3. We proposed a method to disclose the characteristics of comment description, by analyzing structure of comment sentences extracted from source program.4. We proposed a method to divide compound words of KANA, which appear frequently in technical document in Japanese.5. We proposed a CASE tool platform support environment which is reusable for a group of programming languages.6. We developed a system that assists identifier naming, deferring the custom of the project. The target of our system is method name of Java. The system extracts the naming custom from existing method names and its documentation comment.7. We proposed a method to assist writing comments in English. The method uses existing comments as the corpus.8. We proposed a corpus search method that automatically identifies structural patterns of sequences of keywords as query, aiming to examine and refine the corpus, by making application of our corpus.

我们的目标是 CASE 工具不仅可以处理用人工语言编写的源程序，还可以处理用自然语言描述的文档。我们的研究结果如下： 1．我们开发了源程序中的注释模型，作为C语言细粒度模型的扩展。 2．我们提出了一种方法，通过使用出现在源程序和文档中的标识符来获取源程序和文档之间的对应关系。我们的方法通过考虑上下文来区分“定义”和“引用”。3。通过分析从源程序中提取的评论语句的结构，提出了一种揭示评论描述特征的方法。 4．我们提出了一种在日语技术文档中经常出现的假名复合词的划分方法。 5．我们提出了一个可被一组编程语言重用的CASE工具平台支持环境。 6．我们开发了一个辅助标识符命名的系统，推迟了项目的定制。我们系统的目标是Java的方法名。系统从现有方法名称及其文档注释中提取命名习惯。7。我们提出了一种辅助用英语撰写评论的方法。该方法使用现有评论作为语料库。8。我们提出了一种语料库搜索方法，自动识别关键词序列的结构模式作为查询，旨在通过应用我们的语料库来检查和细化语料库。