DocumentCode
3137070
Title
Software Metric Estimation: An Empirical Study Using An Integrated Data Analysis Approach
Author
Da Deng ; Purvis, Martin ; Purvis, Martin
Author_Institution
Univ. of Otago, Dunedin
fYear
2007
fDate
9-11 June 2007
Firstpage
1
Lastpage
6
Abstract
Automatic software effort estimation is important for quality management in the software development industry, but it still remains a challenging issue. In this paper we present an empirical study on the software effort estimation problem using a benchmark dataset. A number of machine learning techniques are employed to construct an integrated data analysis approach that extracts useful information from visualisation, feature selection, model selection and validation.
Keywords
learning (artificial intelligence); quality management; software metrics; software quality; automatic software effort estimation; integrated data analysis; machine learning techniques; quality management; software development industry; software metric estimation; Computer industry; Data analysis; Data mining; Data visualization; Machine learning; Principal component analysis; Programming; Quality management; Software engineering; Software metrics; machine learning; software effort estimation;
fLanguage
English
Publisher
ieee
Conference_Titel
Service Systems and Service Management, 2007 International Conference on
Conference_Location
Chengdu
Print_ISBN
1-4244-0885-7
Electronic_ISBN
1-4244-0885-7
Type
conf
DOI
10.1109/ICSSSM.2007.4280207
Filename
4280207
Link To Document