CMU SEI Research Review 2021 Day 2 Artifacts
• Collection
Publisher
Software Engineering Institute
Subjects
Abstract
This collection includes slides and videos from Day 2 of the 2021 SEI Research Review event. These sessions include presentations, lightning talks, and collaboration conversations. Day 2 sessions include Collaboration Conversation on Scalable Assurance of Safety-Critical Systems, Multicore Confidence, Rapid Certifiable Trust, Towards Incremental and Compositionally Verifiable Security for CHIC-Centric Cyber Physical Systems, Combined Analysis for Source Code and Binary Code for Software Assurance, Rapid Adjudication of Static Analysis Alerts During Continuous Integration, and Collaboration Conversation on Digital Engineering.
Collection Items
Collaboration Conversation on Scalable Assurance of Safety-Critical Systems
• Presentation
By Sholom G. Cohen, Jerome Hugues, Sam Procter, Suzanne Miller
Learn how the SEI's Assuring Cyber-Physical Systems team working on model-based techniques to better describe, analyze, and assure systems.
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Multicore Confidence
• Presentation
By Bjorn Andersson
This SEI projects seeks to help organizations take better advantage of multicore processors by improving the confidence in computational timing.
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Rapid Certifiable Trust
• Presentation
By Dionisio de Niz
Rapid Certifiable Trust seeks to scale the use of formal verification to increase the speed of validation and, consequently, the speed of DoD capability fielding.
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Towards Incremental and Compositionally Verifiable Security for CHIC-Centric Cyber Physical Systems
• Presentation
By Amit Vasudevan
The project aims to achieve incremental and compositionally verifiable security for CHIC-centric Cyber Physical Systems (CPS).
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Combined Analysis for Source Code and Binary Code for Software Assurance
• Presentation
By William Klieber
This research highlight how to increase software assurance of binary components by analyzing and repairing functions.
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Rapid Adjudication of Static Analysis Alerts During Continuous Integration
• Presentation
By Lori Flynn
This project developed algorithms and a static analysis classification system for use with continuous integration, enabling more secure software with less effort.
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CMU SEI Research Review 2021