An approach for clone detection in documentation reuse
The paper focuses on the searching method for repetitions in DocBook/DRL or plain text documents. An algorithm has been designed based on software clone detection. The algorithm supports filtering results: clones are rejected if clone length in the group is less than 5 symbols, intersection of clone...
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2014
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sg-smu-ink.sis_research-49862022-08-29T09:13:02Z An approach for clone detection in documentation reuse LUTSIV, Dmitry V. KOZNOV, Dmitry BASIT, Hamid A. OUH, Eng Lieh SMIRNOV, Mikhail N. ROMANOVSKY, Konstantin Y. The paper focuses on the searching method for repetitions in DocBook/DRL or plain text documents. An algorithm has been designed based on software clone detection. The algorithm supports filtering results: clones are rejected if clone length in the group is less than 5 symbols, intersection of clone groups is eliminated, meaningfulness clones are removed, the groups containing clones consisting only of XML are eliminated. Remaining search is supported: found clones are extracted from the documentation, and clone search is repeated. One step is proved to be enough. Adaptive reuse technique of Paul Bassett – Stan Jarzabek has been implemented. A software tool has been developed on the basis of the algorithm. The tool supports setting parameters for repetitions detection and visualization of the obtained results. The tool is integrated into DocLine document development environment, and provides refactoring of documents using found clones. The Clone Miner clone detection utility is used for clones search. The method has been evaluated for Linux Kernel Documentation (29documents, 25000 lines). Five semantic kinds of clones have been selected: terms (abbreviations, one word and two word terms), hyperlinks, license agreements, functionality description, and code examples. 451 meaningful clone groups have been found, average clone length is 4.43 tokens, and average number of clones in a group is 3.56. 2014-01-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/3984 https://ink.library.smu.edu.sg/context/sis_research/article/4986/viewcontent/an_approach.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University software documentation documentation reuse software clone detection adaptive reuse refactoring DocBook DocLine DRL Programming Languages and Compilers Software Engineering |
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software documentation documentation reuse software clone detection adaptive reuse refactoring DocBook DocLine DRL Programming Languages and Compilers Software Engineering LUTSIV, Dmitry V. KOZNOV, Dmitry BASIT, Hamid A. OUH, Eng Lieh SMIRNOV, Mikhail N. ROMANOVSKY, Konstantin Y. An approach for clone detection in documentation reuse |
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The paper focuses on the searching method for repetitions in DocBook/DRL or plain text documents. An algorithm has been designed based on software clone detection. The algorithm supports filtering results: clones are rejected if clone length in the group is less than 5 symbols, intersection of clone groups is eliminated, meaningfulness clones are removed, the groups containing clones consisting only of XML are eliminated. Remaining search is supported: found clones are extracted from the documentation, and clone search is repeated. One step is proved to be enough. Adaptive reuse technique of Paul Bassett – Stan Jarzabek has been implemented. A software tool has been developed on the basis of the algorithm. The tool supports setting parameters for repetitions detection and visualization of the obtained results. The tool is integrated into DocLine document development environment, and provides refactoring of documents using found clones. The Clone Miner clone detection utility is used for clones search. The method has been evaluated for Linux Kernel Documentation (29documents, 25000 lines). Five semantic kinds of clones have been selected: terms (abbreviations, one word and two word terms), hyperlinks, license agreements, functionality description, and code examples. 451 meaningful clone groups have been found, average clone length is 4.43 tokens, and average number of clones in a group is 3.56. |
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text |
author |
LUTSIV, Dmitry V. KOZNOV, Dmitry BASIT, Hamid A. OUH, Eng Lieh SMIRNOV, Mikhail N. ROMANOVSKY, Konstantin Y. |
author_facet |
LUTSIV, Dmitry V. KOZNOV, Dmitry BASIT, Hamid A. OUH, Eng Lieh SMIRNOV, Mikhail N. ROMANOVSKY, Konstantin Y. |
author_sort |
LUTSIV, Dmitry V. |
title |
An approach for clone detection in documentation reuse |
title_short |
An approach for clone detection in documentation reuse |
title_full |
An approach for clone detection in documentation reuse |
title_fullStr |
An approach for clone detection in documentation reuse |
title_full_unstemmed |
An approach for clone detection in documentation reuse |
title_sort |
approach for clone detection in documentation reuse |
publisher |
Institutional Knowledge at Singapore Management University |
publishDate |
2014 |
url |
https://ink.library.smu.edu.sg/sis_research/3984 https://ink.library.smu.edu.sg/context/sis_research/article/4986/viewcontent/an_approach.pdf |
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