dc.contributor.author | Hall, Tracy | |
dc.contributor.author | Beecham, Sarah | |
dc.contributor.author | Bowes, David | |
dc.contributor.author | Gray, David | |
dc.contributor.author | Counsell, Steve | |
dc.date.accessioned | 2011-11-14T10:01:08Z | |
dc.date.available | 2011-11-14T10:01:08Z | |
dc.date.issued | 2011 | |
dc.identifier.citation | Hall , T , Beecham , S , Bowes , D , Gray , D & Counsell , S 2011 , ' Developing Fault-Prediction Models : What the research can show industry ' , IEEE Software , vol. 28 , no. 6 , pp. 96-99 . https://doi.org/10.1109/MS.2011.138 | |
dc.identifier.issn | 0740-7459 | |
dc.identifier.uri | http://hdl.handle.net/2299/6982 | |
dc.description.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. | en |
dc.format.extent | 4 | |
dc.format.extent | 392862 | |
dc.language.iso | eng | |
dc.relation.ispartof | IEEE Software | |
dc.subject | fault-prediction models | |
dc.title | Developing Fault-Prediction Models : What the research can show industry | en |
dc.contributor.institution | School of Computer Science | |
dc.contributor.institution | Science & Technology Research Institute | |
dc.description.status | Peer reviewed | |
dc.identifier.url | http://www.scopus.com/inward/record.url?scp=80054888111&partnerID=8YFLogxK | |
rioxxterms.versionofrecord | 10.1109/MS.2011.138 | |
rioxxterms.type | Journal Article/Review | |
herts.preservation.rarelyaccessed | true | |