Data mining for software engineering

Tao Xie; Suresh Thummalapenta; David Lo; Chao Liu

doi:10.1109/MC.2009.256

Data mining for software engineering

Tao Xie, Suresh Thummalapenta, David Lo, Chao Liu

Research output: Contribution to specialist publication › Article

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.

Original language	English (US)
Pages	55-62
Number of pages	8
Volume	42
No	8
Specialist publication	Computer
DOIs	https://doi.org/10.1109/MC.2009.256
State	Published - 2009
Externally published	Yes

Keywords

Classification algorithms
Computational intelligence
Data mining
Design and test
Heuristic algorithms
Pattern matching
Software
Software algorithms
Software engineering

ASJC Scopus subject areas

Computer Science(all)

Online availability

10.1109/MC.2009.256

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title = "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.",

keywords = "Classification algorithms, Computational intelligence, Data mining, Design and test, Heuristic algorithms, Pattern matching, Software, Software algorithms, Software engineering",

author = "Tao Xie and Suresh Thummalapenta and David Lo and Chao Liu",

note = "Funding Information: This work is supported in part by NSF grant CCF-0725190 and ARO grant W911NF-08-1-0443.",

year = "2009",

doi = "10.1109/MC.2009.256",

language = "English (US)",

volume = "42",

pages = "55--62",

journal = "Computer",

issn = "0018-9162",

publisher = "IEEE Computer Society",

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AU - Xie, Tao

AU - Thummalapenta, Suresh

AU - Lo, David

AU - Liu, Chao

N1 - Funding Information: This work is supported in part by NSF grant CCF-0725190 and ARO grant W911NF-08-1-0443.

PY - 2009

Y1 - 2009

N2 - 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.

AB - 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.

KW - Classification algorithms

KW - Computational intelligence

KW - Data mining

KW - Design and test

KW - Heuristic algorithms

KW - Pattern matching

KW - Software

KW - Software algorithms

KW - Software engineering

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Data mining for software engineering

Abstract

Keywords

ASJC Scopus subject areas

Online availability

Library availability

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