DATA MINING FOR SOFTWARE ENGINEERING.
The article focuses on the increasing application of data mining algorithms by computer software engineers and discusses algorithms for effective mining. The aim of software engineers is to improve software productivity and quality. The challenges of mining software engineering (SE) data are examine...
| Publicado en: | Computer (00189162) Vol. 42; no. 8; pp. 55 - 63 |
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| Autores principales: | , , , |
| Formato: | Artículo |
| Publicado: |
IEEE
Aug2009
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| Materias: | |
| 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=43977812&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 43977812 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00189162 PUT jtl: Computer (00189162) issn: 00189162 maglogo: N pubinfo: dt: Aug2009 vid: 42 iid: 8 pid: 13605 pub: IEEE artinfo: ui: 43977812 10.1109/MC.2009.256 ppf: 55 ppct: 8 formats: tig: atl: DATA MINING FOR SOFTWARE ENGINEERING. aug: au: Xie, Tao Thummalapenta, Suresh Lo, David Liu, Chao affil: North Carolina State University Singapore Management University Microsoft Research su: Data mining Database searching Algorithms Algebra Computer software development sug: subj: Data mining Database searching Algorithms Algebra Computer software development ab: The article focuses on the increasing application of data mining algorithms by computer software engineers and discusses algorithms for effective mining. The aim of software engineers is to improve software productivity and quality. The challenges of mining software engineering (SE) data are examined. The categories of SE data include sequences, graphs and text. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2009 holdings: @attributes: islocal: N |
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