Abstract
After data mining National Aeronautics and Space Administration (NASA) independent verification and validation (IVV (b) an IVV and (c) pruning heuristics describing what tasks to ignore, if the budget cannot accommodate all selected tasks. In ten-way cross-validation experiments, the predictor performs very well indeed: the average f-measure for predicting four classes of issue severity was over 0.9. This predictor is built using public-domain data and software. To the best of our knowledge, this is the first reproducible report of a predictor for issue frequency and severity that can be applied early in the life cycle.
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.
