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Integration of Automated Static Analysis Alert Classification and Prioritization with Auditing Tools: Special Focus on SCALe

May 2019 Technical Report
Lori Flynn, Ebonie McNeil, Aubrie Woods (Carnegie Mellon University), David Svoboda, Derek Leung, Zach Kurtz, Jiyeon Lee (Carnegie Mellon University)

This report summarizes progress and plans for developing a system to perform automated classification and advanced prioritization of static analysis alerts.

Publisher:

Software Engineering Institute

CMU/SEI Report Number

CMU/SEI-2019-TR-007

Abstract

This report summarizes technical progress and plans as of late September 2018 for developing a system to perform automated classification and advanced prioritization of static analysis alerts. Many features and fields have been added to the Source Code Analysis Laboratory (SCALe) static analysis alert auditing tool to support this functionality. This report describes the new features and fields, and how to use them. It also describes the plan to connect this enhanced version of SCALe to an architecture that will provide classification and prioritization via API calls, and provides the API definition that has been developed. A prototype that instantiates the architecture is being developed; future work will complete the prototype and integrate the latest version of SCALe with it.