DMOSS: Open Source Software Documentation Assessment.

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Title: DMOSS: Open Source Software Documentation Assessment.
Authors: Carvalho, Nuno Ramos1 narcarvalho@di.uminho.pt, Simões, Alberto2 ambs@ilch.uminho.pt, Almeida, José João1 jj@di.uminho.pt
Source: Computer Science & Information Systems. Oct2014, Vol. 11 Issue 4, p1191-1207. 17p.
Subjects: Open source software, Software documentation, Computer software development, Software ecosystems, Natural languages
Abstract: Besides source code, the fundamental source of information about open source software lies in documentation, and other non source code files, like README, INSTALL, or How-To files, commonly available in the software ecosystem. These documents, written in natural language, provide valuable information during the software development stage, but also in future maintenance and evolution tasks. DMOSS is a toolkit designed to systematically assess the quality of non source code content found in software packages. The toolkit handles a package as an attribute tree, and performs several tree traverse algorithms through a set of plugins, specialized in retrieving specific metrics from text, gathering information about the software. These metrics are later used to infer knowledge about the software, and composed together to build reports that assess the quality of specific features. This paper discusses the motivations for this work, continues with a description of the toolkit implementation and design goals. This is followed by an example of its usage to process a software package, and the produced report. [ABSTRACT FROM AUTHOR]
Copyright of Computer Science & Information Systems is the property of ComSIS Consortium and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: <searchLink fieldCode="JN" term="%22Computer+Science+%26+Information+Systems%22">Computer Science & Information Systems</searchLink>. Oct2014, Vol. 11 Issue 4, p1191-1207. 17p.
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  Data: <searchLink fieldCode="DE" term="%22Open+source+software%22">Open source software</searchLink><br /><searchLink fieldCode="DE" term="%22Software+documentation%22">Software documentation</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+software+development%22">Computer software development</searchLink><br /><searchLink fieldCode="DE" term="%22Software+ecosystems%22">Software ecosystems</searchLink><br /><searchLink fieldCode="DE" term="%22Natural+languages%22">Natural languages</searchLink>
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  Data: Besides source code, the fundamental source of information about open source software lies in documentation, and other non source code files, like README, INSTALL, or How-To files, commonly available in the software ecosystem. These documents, written in natural language, provide valuable information during the software development stage, but also in future maintenance and evolution tasks. DMOSS is a toolkit designed to systematically assess the quality of non source code content found in software packages. The toolkit handles a package as an attribute tree, and performs several tree traverse algorithms through a set of plugins, specialized in retrieving specific metrics from text, gathering information about the software. These metrics are later used to infer knowledge about the software, and composed together to build reports that assess the quality of specific features. This paper discusses the motivations for this work, continues with a description of the toolkit implementation and design goals. This is followed by an example of its usage to process a software package, and the produced report. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Computer Science & Information Systems is the property of ComSIS Consortium and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.2298/CSIS131005027C
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              Text: Oct2014
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