Brunel University Research Archive(BURA) preserves and enables easy and open access to all
types of digital content. It showcases Brunel's research outputs.
Research contained within BURA is open access, although some publications may be subject
to publisher imposed embargoes. All awarded PhD theses are also archived on BURA.
Please use this identifier to cite or link to this item:
http://bura.brunel.ac.uk/handle/2438/20524| Title: | Assessing software defection prediction performance: why using the Matthews correlation coefficient matters |
| Authors: | Yao, J Shepperd, M |
| Keywords: | software engineering experimentation;software defect prediction;classification metrics |
| Issue Date: | 15-Apr-2020 |
| Publisher: | Association for Computing Machinery |
| Citation: | Jingxiu Yao and Martin Shepperd (2020) 'Assessing software defection prediction performance: why using the Matthews correlation coefficient matters', in Proceedings of the Evaluation and Assessment in Software Engineering (EASE 2020), April 15–17, 2020, Trondheim, Norway. ACM, New York, NY, USA, 120-129. doi: 10.1145/3383219.3383232. |
| URI: | https://bura.brunel.ac.uk/handle/2438/20524 |
| DOI: | https://doi.org/10.1145/3383219.3383232 |
| Appears in Collections: | Dept of Computer Science Research Papers |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| FullText.pdf | 1.16 MB | Adobe PDF | View/Open |
Items in BURA are protected by copyright, with all rights reserved, unless otherwise indicated.