June 23, 2022
The article titled “Static Code Analysis Alarms Filtering Reloaded: A New Real-World Dataset and its ML-Based Utilization” written by Péter Hegedűs and Rudolf Ferenc has been accepted into IEEE Access.
The paper introduces the most extensive public dataset and study to-date aiming to aid the filtering of false-positive results in Static Code Analysis (SCA); a collection of 224000+ samples datamined from over 9900 different open-source Java projects.
The article can be read in IEEE’s online library
Page last modified: June 23, 2022