The study explores the risks and tradeoffs when adapting enterprise-IT security and zero trust principles to weapon systems.
DeCapria, D., 2025: DataOps: Towards More Reliable Machine Learning Systems. Carnegie Mellon University, Software Engineering Institute's Insights (blog), Accessed ...
The Software Engineering Institute is a leader in researching complex solutions, connecting AI, cyber, and software strategies for maximum impact. Since 1984, the SEI has been one of only 10 Federally ...
Robert, J., and Schmidt, D., 2024: 10 Benefits and 10 Challenges of Applying Large Language Models to DoD Software Acquisition. Carnegie Mellon University, Software ...
Robinson, K., and Turri, V., 2024: Auditing Bias in Large Language Models. Carnegie Mellon University, Software Engineering Institute's Insights (blog), Accessed ...
Shevchenko, N., 2018: Threat Modeling: 12 Available Methods. Carnegie Mellon University, Software Engineering Institute's Insights (blog), Accessed October 29, 2025 ...
DeCapria, D., 2024: Introduction to MLOps: Bridging Machine Learning and Operations. Carnegie Mellon University, Software Engineering Institute's Insights (blog ...
Shevchenko, N., 2024: An Introduction to Model-Based Systems Engineering (MBSE). Carnegie Mellon University, Software Engineering Institute's Insights (blog ...
Ozkaya, I., and Schmidt, D., 2024: Generative AI and Software Engineering Education. Carnegie Mellon University, Software Engineering Institute's Insights (blog ...
Firesmith, D., 2019: System Resilience: What Exactly is it?. Carnegie Mellon University, Software Engineering Institute's Insights (blog), Accessed October 29, 2025 ...
Yankel, J., 2024: Example Case: Using DevSecOps to Redefine Minimum Viable Product. Carnegie Mellon University, Software Engineering Institute's Insights (blog ...