Automatically Finding Web Documents Related to a Code Sample

• Item type: SIG Technical Reports(1)
• 公開日: 2010-03-11
• タイトル: Automatically Finding Web Documents Related to a Code Sample
• タイトル / 言語: en
• タイトル: Automatically Finding Web Documents Related to a Code Sample
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: 保守・解析（学生セッション）
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_18gh
• 資源タイプ: technical report
• 著者所属: Graduate School of Science and Engineering, Ritsumeikan University
• 著者所属: Department of Computer Science, Ritsumeikan University
• 著者所属(英): en
• 著者所属(英): Graduate School of Science and Engineering, Ritsumeikan University
• 著者所属(英): en
• 著者所属(英): Department of Computer Science, Ritsumeikan University
• 著者名: PhanTheDai; Katsuhisa, Maruyama
• 著者名(英): Phan, TheDai; Katsuhisa, Maruyama
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: Code search engines on Web have played important roles for novice programmers during developing software or studying programming by reference examples. However, they have faced a problem from search results because these code samples lack context or can be unfamiliar code snippets that are incomprehensible. They must find external information resources by using another Web search engine with numerous queries manually and too many pages can be visited. This paper presents a method to automatically find related Web documents to support them to comprehend source code. We utilize Web search service APIs for collecting related information of Web pages to process. Advantaged techniques of information retrieval are used to rank the text documents. For demonstrating benefits of this method, the proposed method is applied into an architecture model of a source code search engine and its implementation. Experimental results from several case studies showed that the method is useful in supporting programmers understanding new concepts in code samples.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: Code search engines on Web have played important roles for novice programmers during developing software or studying programming by reference examples. However, they have faced a problem from search results because these code samples lack context or can be unfamiliar code snippets that are incomprehensible. They must find external information resources by using another Web search engine with numerous queries manually and too many pages can be visited. This paper presents a method to automatically find related Web documents to support them to comprehend source code. We utilize Web search service APIs for collecting related information of Web pages to process. Advantaged techniques of information retrieval are used to rank the text documents. For demonstrating benefits of this method, the proposed method is applied into an architecture model of a source code search engine and its implementation. Experimental results from several case studies showed that the method is useful in supporting programmers understanding new concepts in code samples.
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AN10112981
• 書誌情報: 研究報告ソフトウェア工学（SE）; 巻 2010-SE-167, 号 7, p. 1-8, 発行日 2010-03-11
• Notice: SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc.
• 出版者 / 言語: ja
• 出版者: 情報処理学会