Mining and discovery of hidden relationships between software source codes and related textual documents.
Normally, software documentations are produced, informally. They are written in the unnatural and non-structural form of the language, such as user manuals, user requirements, design documentation, tutorials, support documentation, and so on. Recent studies show that 61% of software projects are sub...
| Publicado en: | Digital Scholarship in the Humanities Vol. 33; no. 3; pp. 651 - 670 |
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| Autores principales: | , , , |
| Formato: | Artículo |
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Oxford University Press / USA
Sep2018
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=131417027&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 131417027 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 2055768X JEO9 jtl: Digital Scholarship in the Humanities issn: 2055768X maglogo: N pubinfo: dt: Sep2018 vid: 33 iid: 3 pid: 622 pub: Oxford University Press / USA artinfo: ui: 131417027 10.1093/llc/fqx052 ppf: 651 ppct: 19 formats: fmt: – @attributes: type: T – @attributes: type: P size: 1.3MB tig: atl: Mining and discovery of hidden relationships between software source codes and related textual documents. aug: au: Rasekh, Amir Hossein Arshia, Amir Hossein Fakhrahmad, Seyed Mostafa Sadreddini, Mohammad Hadi affil: Shiraz University, Iran su: Source code Software documentation Computer software development Software architecture Natural language processing sug: subj: Source code Software documentation Computer software development Software architecture Natural language processing ab: Normally, software documentations are produced, informally. They are written in the unnatural and non-structural form of the language, such as user manuals, user requirements, design documentation, tutorials, support documentation, and so on. Recent studies show that 61% of software projects are subject to failure or challenges due to an increase in the costs and production time. Various factors may lead to this issue, and one of the major contributing factors is the lack of links between the software's source code and its related documents. The significance of software development and the possibility of making prospective changes by the development team necessitate an understanding of the links between various sections of codes and documentations. Therefore, it is crucial to design a system to link the software codes to their corresponding textual documentation. This article proposes a model for recovering the latent, but traceable links between software source codes and existing documents based on word extraction and function name separation. The contributions in this article include: (1) a model based on word extraction from document and source codes; (2) the proposal of an algorithm for splitting compound words and words that are connected to one another and completing abbreviations used in the names of functions, variables, and output commands; and (3) a new algorithm that is proposed for retrieving traceable latent links between the source code and documents. Two data sets are used in this research and the achieved results will be reported in terms of recall, precision, and F -measure. The experimental results are promising and indicate that the proposed approach significantly outperforms its counterparts. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: © 2019 EADH: The European Association for Digital Humanities. item: Digital Scholarship in the Humanities holder: Oxford University Press / USA dt: @attributes: year: 2018 holdings: @attributes: islocal: N |
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