A measurement framework of alert characteristics for false positive mitigation models
Sarah Smith Heckman, Laurie A. Williams · NCSU Libraries Repository (North Carolina State University Libraries) · 2008
Automated static analysis tools can be used to identify potential source code anomalies early in the software process that could lead to field failures.However, only a small portion of static analysis alerts may be important to the developer (actionable).The remainder are false positives (unactionable).Static analysis tools may generate an overwhelming number of alerts, the majority of which are likely to be unactionable.False positive mitigation techniques utilize information about static analysis alerts, called alert characteristics, to predict actionable and unactionable alerts.This paper presents a measurement framework for generating static analysis alert characteristics for false positive mitigation models.