New approaches will be required to enable intellectual control at an entirely new level of scope and scale for system analysis, design, and operation.
ULS systems will be defined in many languages, each with its own abstractions and semantic structures. This research area focuses on evolving the expressiveness of representations to accommodate this semantic diversity. Because the complexity of ULS systems will challenge human comprehension, this area also focuses on providing automated support for computing the behavior of components and their compositions in systems and for maintaining desired properties as ULS systems evolve.
abstraction |
machine learning |
Mernik, M.; Heering, J.; & Sloane, A. “When and how to develop domain-specific languages.” ACM Computing Surveys 37, 4 (2005): 316–344.
Neumann, P. Principled Assuredly Trustworthy Composable Architectures (SRI Project 11459, Final Report). Menlo Park, CA: Computer Science Laboratory, SRI International, June 28, 2003.
Pleszkoch, M. & Linger, R. “Improving Network System Security with Function Extraction Technology for Automated Computation of Program Behavior.” Proceedings of the 37th Hawaii International Conference on System Sciences (HICSS-37), Kona, HI. IEEE Computer Society Press, 2004.
Prowell, S.; Trammell, C. J.; Linger, R.; & Poore, J. H. Cleanroom Software Engineering: Technology and Process. SEI Series in Software Engineering. Reading, MA: Addison-Wesley Longman, 1999.
Read Greg Goth's May 2008 IEEE Software article: "Ultralarge Systems: Redefining Software Engineering?"
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