Developing fault-prediction models: What the research can show industry

Tracy Hall; Sarah Beecham; David Bowes; David Gray; Steve Counsell

doi:10.1109/MS.2011.138

Developing fault-prediction models: What the research can show industry

Tracy Hall, Sarah Beecham, David Bowes, David Gray, Steve Counsell

Research output: Contribution to journal › Article › peer-review

Abstract

A systematic review of the research literature on fault-prediction models from 2000 through 2010 identified 36 studies that sufficiently defined their models and development context and methodology. The authors quantitatively analyzed 19 of these studies and the 206 models they presented. They identified several key features to help industry software developers build or optimize fault-prediction models suitable to their specific contexts.

Original language	English
Article number	6055666
Pages (from-to)	96-99
Number of pages	4
Journal	IEEE Software
Volume	28
Issue number	6
DOIs	https://doi.org/10.1109/MS.2011.138
Publication status	Published - Nov 2011
Externally published	Yes

Keywords

fault-prediction models

Access to Document

10.1109/MS.2011.138

Cite this

@article{b69f133524374899ab257d80acd85765,

title = "Developing fault-prediction models: What the research can show industry",

abstract = "A systematic review of the research literature on fault-prediction models from 2000 through 2010 identified 36 studies that sufficiently defined their models and development context and methodology. The authors quantitatively analyzed 19 of these studies and the 206 models they presented. They identified several key features to help industry software developers build or optimize fault-prediction models suitable to their specific contexts.",

keywords = "fault-prediction models",

author = "Tracy Hall and Sarah Beecham and David Bowes and David Gray and Steve Counsell",

year = "2011",

month = nov,

doi = "10.1109/MS.2011.138",

language = "English",

volume = "28",

pages = "96--99",

journal = "IEEE Software",

issn = "0740-7459",

number = "6",

}

TY - JOUR

T1 - Developing fault-prediction models

T2 - What the research can show industry

AU - Hall, Tracy

AU - Beecham, Sarah

AU - Bowes, David

AU - Gray, David

AU - Counsell, Steve

PY - 2011/11

Y1 - 2011/11

N2 - A systematic review of the research literature on fault-prediction models from 2000 through 2010 identified 36 studies that sufficiently defined their models and development context and methodology. The authors quantitatively analyzed 19 of these studies and the 206 models they presented. They identified several key features to help industry software developers build or optimize fault-prediction models suitable to their specific contexts.

AB - A systematic review of the research literature on fault-prediction models from 2000 through 2010 identified 36 studies that sufficiently defined their models and development context and methodology. The authors quantitatively analyzed 19 of these studies and the 206 models they presented. They identified several key features to help industry software developers build or optimize fault-prediction models suitable to their specific contexts.

KW - fault-prediction models

UR - http://www.scopus.com/inward/record.url?scp=80054888111&partnerID=8YFLogxK

U2 - 10.1109/MS.2011.138

DO - 10.1109/MS.2011.138

M3 - Article

AN - SCOPUS:80054888111

SN - 0740-7459

VL - 28

SP - 96

EP - 99

JO - IEEE Software

JF - IEEE Software

IS - 6

M1 - 6055666

ER -

Developing fault-prediction models: What the research can show industry

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this