@inproceedings{016d2eae8e174290962a5b8ac439485f,
title = "Prest: An intelligent software metrics extraction, analysis and defect prediction tool",
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.",
author = "Ekrem Kocag{\"u}neli and Ay{\c s}e Tosun and Ay{\c s}e Bener and Burak Turhan and Bora {\c C}ǧlayan",
year = "2009",
language = "English",
isbn = "1891706241",
series = "Proceedings of the 21st International Conference on Software Engineering and Knowledge Engineering, SEKE 2009",
pages = "637--642",
booktitle = "Proceedings of the 21st International Conference on Software Engineering and Knowledge Engineering, SEKE 2009",
note = "21st International Conference on Software Engineering and Knowledge Engineering, SEKE 2009 ; Conference date: 01-07-2009 Through 03-07-2009",
}