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https://dx.doi.org/10.1109/mc....
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Data Mining for Software Engineering

descriptionPublicationkeyboard_double_arrow_right Article 01 Aug 2009 Singapore Publisher:Institute of Electrical and Electronics Engineers (IEEE)Journal:Computer, volume 42, pages 55-62 (issn: 0018-9162, Copyright policy )
Authors: Tao Xie 0001; Suresh Thummalapenta; David Lo 0001; Chao Liu 0001;

doi: 10.1109/mc.2009.256

Data Mining for Software Engineering

Abstract

To improve software productivity and quality, software engineers are increasingly applying data mining algorithms to various software engineering tasks. However, mining SE data poses several challenges. The authors present various algorithms to effectively mine sequences, graphs, and text from such data.

Country
Singapore
Related Organizations
Keywords

Computational intelligence, Software engineering, Design and test, Data mining

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    		 84
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    		 Top 10%
    influence
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
84
Top 10%
Top 1%
Top 10%
Green
hybrid