All Projects
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A Tool Set to Support Big Data Systems Acquisition
We offer an approach that reduces risk and simplifies the selection and acquisition of big data technologies when you acquire and develop big data systems.
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Acquiring Systems, Not Just Software
The U.S. Department of Defense (DoD) and federal agencies are increasingly acquiring software-intensive systems instead of building them with internal resources. However, acquisition programs frequently have difficulty identifying the critical software acquisition activities, deliverables, risks, and opportunities.
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AI Engineering: A National Initiative
The SEI is taking the initiative to develop an AI engineering discipline that will lay the groundwork for establishing the practices, processes, and knowledge to build new generations of AI solutions.
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AI Trust Lab: Engineering for Trustworthy AI
The SEI’s Trust Lab advances the development of trustworthy AI through accelerated research and collaboration. We develop frameworks, tools, and guidelines driven by trustworthy, human-centered, and responsible AI engineering practices.
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AI Workforce Development
The SEI is advancing the professional discipline of AI engineering through the latest academic advancements at Carnegie Mellon University.
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AISIRT Ensures the Safety of AI Systems
The SEI created an AISIRT to ensure that organizations develop, adopt, and use AI effectively and safely to safeguard the security of the nation.
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An Innovative Approach to Internet of Things (IoT) Security at the Edge
Internet of Things (IoT) devices can provide useful capabilities, but many have known security vulnerabilities that have been exploited by malicious actors. The SEI KalKi security platform leverages software-defined networking (SDN) and network function virtualization (NFV) to enable secure integration of IoT devices into Department of Defense (DoD) networks, even devices that are not fully trusted or configurable.
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Applying Causal Learning to Improve Software Cost Estimation and Project Control
SEI researchers have applied causal learning to help the Department of Defense identify factors that increase software costs and to provide guidance to control them.
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Architecting the Future of Software Engineering: A National Agenda for Software Engineering Research & Development
This study identifies the technologies and areas of research that are most critical for enabling future software systems. The technology roadmap that resulted from this work is intended to guide the research efforts of the software engineering community toward future systems that are safe, predictable, and evolvable.
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Architecture Analysis and Design Language (AADL)
Software for mission- and safety-critical systems, such as avionics systems in aircraft, is growing larger and more expensive. The Architecture Analysis and Design Language (AADL) addresses common problems in the development of these systems, such as mismatched assumptions about the physical system, computer hardware, software, and their interactions that can result in system problems detected too late in the development lifecycle.
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