Detecting false alarms from automatic static analysis tools: how far are we?

• Main Authors: KANG, Hong Jin, AW, Khai Loong, LO, David
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2022
• Subjects: Static analysis; False alarms; Data leakage; Data duplication; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/7686; https://ink.library.smu.edu.sg/context/sis_research/article/8689/viewcontent/detecting.pdf
• Institution: Singapore Management University

Automatic static analysis tools (ASATs), such as Findbugs, have a high false alarm rate. The large number of false alarms produced poses a barrier to adoption. Researchers have proposed the use of machine learning to prune false alarms and present only actionable warnings to developers. The state-of...