When to use data from other projects for effort estimation

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)

32 Scopus Citations
View graph of relations

Author(s)

Detail(s)

Original languageEnglish
Title of host publicationASE'10 - Proceedings of the IEEE/ACM International Conference on Automated Software Engineering
Pages321-324
Publication statusPublished - 2010
Externally publishedYes

Conference

Title25th IEEE/ACM International Conference on Automated Software Engineering, ASE'10
PlaceBelgium
CityAntwerp
Period20 - 24 September 2010

Abstract

Collecting the data required for quality prediction within a development team is time-consuming and expensive. An alternative to make predictions using data that crosses from other projects or even other companies. We show that with/without relevancy filtering, imported data performs the same/worse (respectively) than using local data. Therefore,we recommend the use of relevancy filtering whenever generating estimates using data from another project. © 2010 ACM.

Research Area(s)

  • Cross, Data mining, Effort estimation, Within

Citation Format(s)

When to use data from other projects for effort estimation. / Kocaguneli, Ekrem; Gay, Gregory; Menzies, Tim; Yang, Ye; Eung, Jacky W.K.

ASE'10 - Proceedings of the IEEE/ACM International Conference on Automated Software Engineering. 2010. p. 321-324.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)