2024 Research Review
Towards Compositional Assurance of Large-Scale Systems
Assuring evolving large-scale systems (i.e., systems with multiple subsystems) can be a bottleneck in deploying capabilities with the speed and confidence needed for current Department of Defense (DoD) missions. There is no easy way to automatically integrate the complex web of interacting assurance techniques (i.e., for control stability, timing, security, logical correctness, and more) from multiple interacting subsystems in a system. In addition, without awareness of assurance interdependencies and effective reuse of prior assurance, the cost and time required for re-assurance can skyrocket.
Our objective is to develop the representations, algorithms, and associated tooling for automatically capturing and evaluating an argument architecture for a system from the argument architectures of its subsystems.
Dr. Gabriel MorenoPrincipal Researcher
Re-assurance remains an unresolved challenge in realizing almost all DoD initiatives aimed at rapidly delivering combat system capabilities. To address this problem, our project will use the concept of formal argument architecture: an artifact that imparts structure to the set of interacting assurance analyses needed to show that a system is ready for fielding and allows reasoning over the composition of those analyses.
Our objective is to develop the representations, algorithms, and associated tooling for automatically capturing and evaluating an argument architecture for a system from the argument architectures of its subsystems. This will accelerate assurance by reusing verification results of subsystems to assure global system properties and increase assurance confidence by using formal proof techniques. Achieving this objective requires developing a vehicle for composing assurance techniques with varying levels of trust in a manner that preserves the soundness of the results. We have developed a logic that supports rely-guarantee reasoning even when different levels of trusts are involved. We believe this is key to formally integrating different kinds of analysis results. The sound reuse of assurance results will remove one of the barriers to achieve the capability to deliver speed that the DoD needs.
In Context: This FY2024-25 Project
- is a collaborative effort utilizing researchers from the Software Engineering Institute (SEI) and Carnegie Mellon University (CMU) building on previous SEI line-funded projects, including the FY22 Ensuring Transition of Model-based Engineering Using Assurance Contracts (ETMAC), and FY23 Formal Arguments for Large-Scale Assurance (FALSA) projects
- leverages SEI expertise and experience in the development of reasoning frameworks for different quality attributes, including performance and security, software architecture analysis, formal analysis contracts, runtime assurance, and systems development
- aligns with the CMU SEI focus on the enduring challenge of improving the trustworthiness of systems
- aligns with the Office of the Under Secretary of Defense for Research and Engineering (OUSD(R&E)) critical technology priority of leveraging advanced computing and software
Principal Investigator
Dr. Gabriel Moreno
Principal Researcher
SEI Collaborators
Mark Klein
Principal Technical Advisor
Dr. Shambwaditya Saha
Assurance Researcher
Dr. Anton Hristozov
Senior Engineer
John Robert
Division Deputy Director
Dr. Dionisio de Niz
Technical Director, Assuring CyberPhysical Systems
CMU Collaborators
Dr. Ruben Martins
Assistant Professor
Computer Science Department
Dr. Limin Jia
Research Professor
Department of Electrical and Computer Engineering
External Collaborators
Dr. Farzaneh Derakhshan
Assistant Professor
Illinois Institute of Technology
Have a Question?
Reach out to us at info@sei.cmu.edu.