Prest: An intelligent software metrics extraction, analysis and defect prediction tool

Ekrem Kocagüneli, Ayşe Tosun, Ayşe Bener, Burak Turhan, Bora Çǧlayan

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

20 Citations (Scopus)

Abstract

Test managers use intelligent predictors to increase testing efficiency and to decide on when to stop testing. However, those predictors would be impractical to use in an industry setting, unless measurement and prediction processes are automated. Prest as an open source tool aims to address this problem. Compared to other open source prediction and analysis tools Prest is unique that it collects source code metrics and call graphs in 5 different programming languages, and performs learning based defect prediction and analysis. So far Prest in real life industry projects helped companies to achieve an average of 32% efficiency increase in testing effort.

Original languageEnglish
Title of host publicationProceedings of the 21st International Conference on Software Engineering and Knowledge Engineering, SEKE 2009
Pages637-642
Number of pages6
Publication statusPublished - 1 Dec 2009
Externally publishedYes
Event21st International Conference on Software Engineering and Knowledge Engineering, SEKE 2009 - Boston, United States of America
Duration: 1 Jul 20093 Jul 2009

Conference

Conference21st International Conference on Software Engineering and Knowledge Engineering, SEKE 2009
CountryUnited States of America
CityBoston
Period1/07/093/07/09

Cite this

Kocagüneli, E., Tosun, A., Bener, A., Turhan, B., & Çǧlayan, B. (2009). Prest: An intelligent software metrics extraction, analysis and defect prediction tool. In Proceedings of the 21st International Conference on Software Engineering and Knowledge Engineering, SEKE 2009 (pp. 637-642)