Abstract
This paper analyzes the ability of requirement metrics for software defect prediction. Statistical significance tests are used to compare six machine learning algorithms on the requirement metrics, design metrics, and combination of both metrics in our analysis. The experimental results show the effectiveness of the predictor built on the combination of the requirement and design metrics in the early phase of the software development process.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
