In March, the secretary of protection directed the Division of Protection (DoD) to undertake the Software program Acquisition Pathway (SWP) to speed up the event and deployment of capabilities to the warfighter. The mandate to make use of the SWP, which the SEI contributed to, arrives at a time when DoD missions more and more depend on software program and the associated applied sciences of cybersecurity and synthetic intelligence (AI)—all of that are focus areas on the SEI. These technical areas develop in significance as nationwide safety and protection organizations require enhanced capabilities to guard a broader vary of targets towards extra refined and adept threats.
On this submit, I’ll spotlight the methods by which our analysis and improvement help DoD’s use of contemporary software program practices at every part of the software program improvement and operation lifecycle.
The SEI and the Software program Acquisition Pathway
The SEI’s depth of expertise with data-driven strategies, strategies, and approaches; software program engineering; and acquisition science catalyzed our work on the SWP.
Part 255 of the FY2020 Nationwide Protection Authorization Act (NDAA) known as on the DoD to orient its software program actions in analysis, improvement, testing, and acquisition towards fashionable software program engineering practices described in two research that SEI additionally contributed to: the Protection Innovation Board’s 2019 Software program Acquisition and Practices (SWAP) and the Protection Science Board Process Power’s 2018 Design and Acquisition of Software program for Protection Techniques.
As a part of our SWP work, the SEI labored hand-in-hand with stakeholders throughout the DoD and the protection industrial base within the iterative improvement, testing, and updating of the coverage and supporting instruments and assets. As known as for within the coverage doc DoDI 5000.87, DoD applications are to emphasise risk-based cybersecurity all through the lifecycle, counting on fashionable software program practices together with DevSecOps. Cybersecurity and DevSecOps kind a basis on which these applications can incorporate new AI applied sciences extra securely.
Because the SEI’s inception as a federally funded analysis and improvement heart (FFRDC), now we have labored with academia, authorities, and trade to conduct analysis and assist DoD applications apply these important instruments, strategies, practices, and insurance policies. The SEI prioritizes improvement of strategies to help steady, resilient, and well timed deployment of software program functionality for the warfighter whereas making certain that software program system efficiency and safety are usually not compromised in mission-critical settings.
SEI Influence on Modernizing DoD Software program Improvement
During the last decade, the DoD has been incorporating rules and practices that promote steady, iterative deployment of software program functionality. One such initiative was the event of the 250-plus member Agile Collaboration Group. Members share classes discovered to assist DoD practitioners extra readily profit from utilizing Agile strategies of their larger-scale techniques. When the group started in 2012, it centered on overcoming adoption challenges round Agile. In 2017, it expanded into DevSecOps analysis, improvement, and discipline engagement.
In 2024 the SEI carried out a examine of the state of DevSecOps within the DoD, the outcomes of which had been just lately launched by the DoD Chief Info Officer (CIO). The examine discovered that whereas sure applications have had success adopting DevSecOps practices, the DoD nonetheless must implement these successes at scale. The examine holds partially that
- Investing in DoD software program factories is vital to securing our future functionality.
- DevSecOps is a key technique to speed up supply time.
- Success rests on reimagining a mission-ready DevSecOps workforce.
- Sturdy management dedicated to creatively driving options is crucial to overcoming obstacles.
The DevSecOps examine additionally acknowledges that it’s essential to align these practices with the mission.
To a major diploma, the efficient use of contemporary software program practices rests on recognizing the strategic worth of knowledge that’s now obtainable to the DoD in more and more huge quantities. To provide DoD analysts better visibility into DevSecOps pipeline knowledge, the SEI just lately launched Polar, an answer to the restrictions of conventional batch knowledge processing. Polar offers visibility into the present state of a company’s DevSecOps infrastructure, permitting for the whole thing of the info to be engaged for knowledgeable choice making. The Polar framework, which could be downloaded from the SEI’s GitHub website, helps DevSecOps organizations monitor and achieve insights into safety features and deal with the challenges posed by constructing complicated software program techniques in extremely regulated environments.
DoD program leaders should more and more handle the entire software program improvement functionality. This accountability usually means dealing successfully with the technical debt that may accumulate in growing older techniques in addition to that which may accumulate in fast, iterative improvement. The SEI has been a pioneer in creating and making use of technical debt administration practices in complicated techniques for nationwide safety and protection. Starting in 2010, the SEI challenged the software program engineering analysis neighborhood to search out methods to handle technical debt and convened annual workshops on the subject. These workshops produced case research, empirical outcomes from making use of strategies, and comparisons of instruments shared by the SEI and the software program neighborhood in tons of of publications within the Affiliation for Computing Equipment (ACM) and IEEE digital libraries. In 2018, the SEI’s neighborhood efforts resulted within the first worldwide convention on the topic, TechDebt. The eighth TechDebt convention was held in April 2025.
The SEI additionally led by way of ground-breaking analysis on the subject. An early paper on the subject, In Search of a Metric for Managing Architectural Debt, authored by SEI and College of British Columbia researchers, obtained the Most Influential Paper Award for its lasting influence on software program structure analysis and follow on the 2022 IEEE Worldwide Convention on Software program Structure. The SEI’s experience in technical debt R&D is the rationale that the DoD commissioned a crew of our software program improvement specialists to jot down a report addressing the NDAA 2022 Part 835 mandate, delivered to Congress in December 2023.
The SEI has used its function to allow the DoD’s efficient use of contemporary software program engineering practices in different methods, as effectively, together with instruments to
SEI Influence on Modernizing DoD Software program in Operation
A core tenet of the SEI’s mission is to allow the DoD to quickly deploy resilient software program capabilities. To do that, they want the appropriate tooling to make use of fashionable software program practices and the means to guarantee system efficiency.
To facilitate DevSecOps use with large-scale techniques, the SEI created the Platform-Impartial Mannequin (PIM)—obtainable on the SEI’s GitHub website—to explain a DevSecOps pipeline on the highest stage: necessities, the product improvement lifecycle course of, and the organizational roles wanted to supply software program. Since its launch, a cross-disciplinary SEI crew has enhanced the PIM by incorporating risk eventualities: assault sort, actors, results, and pipeline property for defense. The ensuing upgraded instruments can be utilized to create safer processes and pipelines or spot safety weaknesses in current ones. When the pipeline is safer, so too is the software program it produces.
To enhance software program threat evaluation, SEI researchers and power builders just lately launched an open-source device that streamlines and automates high quality assurance testing and evaluation, Silent Sentinel. This device supplies a repeatable, constant course of to offer system stakeholders a practical evaluation of how an utility will have an effect on their deployment surroundings.
Steady supply of software program functionality additionally signifies that techniques utilizing these capabilities want steady assurance of security, safety, and different qualities. In ongoing work, the SEI is in search of to cut back the effort and time required to re-assure giant techniques. This notion of system assurance extends past safety to embody a number of architecturally important issues, together with efficiency, modifiability, security, and reliability.
SEI Influence on AI System Assurance
The world, and definitely the DoD’s expertise surroundings, is turning into more and more AI-augmented. When AI techniques for nationwide safety fail in improvement or operation, they trigger critical, real-world penalties. Sadly, there are few accepted greatest practices for testing AI techniques because of the challenges of correctly defining necessities and evaluating standards.
In 2023, the Workplace of the Beneath Secretary of Protection for Analysis and Engineering (OUSD(R&E)) and the SEI launched a middle geared toward establishing strategies for assuring trustworthiness in AI techniques with emphasis on interplay between people and autonomous techniques. The Middle for Calibrated Belief Measurement and Analysis (CaTE) goals to assist the DoD be certain that AI techniques are protected, dependable, and reliable earlier than being fielded to operators in crucial conditions.
Additional, as detailed in a latest weblog submit and podcast, a gaggle of SEI software program and AI specialists just lately launched Machine Studying Check and Analysis (MLTE), a brand new course of and power collectively developed by the SEI and the Military AI Integration Middle (AI2C) to create safer, extra dependable ML techniques. MLTE addresses three issues frequent within the ML mannequin improvement course of which can be obstacles to efficient take a look at and analysis processes.
- Communication obstacles between product improvement crew members. Staff members are sometimes siloed throughout organizations, resulting in issues in gathering ML mannequin necessities cognizant of the system context and speaking ML mannequin analysis outcomes.
- Documentation issues for ML mannequin necessities. Eliciting and documenting ML mannequin necessities is commonly a problem for organizations, and documentation for ML system necessities is commonly lacking or of low high quality.
- Requirement analysis. Even when necessities are correctly outlined and documented, there isn’t any ML-specific methodology to help their implementation, testing, and analysis.
Broadening our perspective to AI threat administration, we explored easy methods to conceptualize fashionable AI threat administration frameworks (RMFs) analogous to these for cyber threat. This work illustrates the broad scope of challenges that AI Engineering practices should deal with, together with software program engineering and cybersecurity concerns. A latest SEI weblog submit famous this:
We should take into account, in different phrases, the habits of a system or an related workflow below each anticipated and surprising inputs, the place these inputs could also be significantly problematic for the system. It’s difficult, nonetheless, even to border the query of easy methods to specify behaviors for anticipated inputs that aren’t precisely matched within the coaching set. A human observer could have an intuitive notion of similarity of recent inputs with coaching inputs, however there isn’t any assurance that this aligns with the precise that includes—the salient parameter values—inside to a skilled neural community.
SEI analysis groups additionally noticed the necessity for an AI safety response crew analogous to laptop safety response. An knowledgeable and motivated attacker could intentionally manipulate operational inputs, coaching knowledge, and different features of the system improvement course of to create circumstances that impair right operation of an AI system. To deal with this want, the SEI launched the first-of-its type AI Safety Incident Response Staff (AISIRT).
To guarantee that future AI techniques can be strong, safe, scalable, and able to serving warfighter wants, the SEI has been main the initiative to advance the self-discipline of AI Engineering. This emergent self-discipline will allow practitioners to focus R&D efforts in AI on creating instruments, techniques, and processes for nationwide safety contexts.
SEI Influence on Software program Acquisition Safety
Nearly all services {that a} DoD program acquires are supported by or combine with info expertise that features third-party elements or providers. Practices crucial to monitoring and managing these dangers could be scattered, leading to inconsistencies, gaps, and gradual response to disruptions. To deal with these points, SEI researchers created the Acquisition Safety Framework (ASF), which supplies the DoD with a roadmap for constructing safety and resilience right into a system relatively than bolting them on after deployment. The ASF promotes higher communication and knowledge sharing throughout all program and provider groups to coordinate their administration of engineering and provide chain dangers. On this means, the ASF helps applications match threats in a dynamic surroundings with the fast evolution of wanted software program capabilities.
As well as, in early 2020 the SEI partnered with Johns Hopkins College Utilized Physics Laboratory (APL), a college affiliated analysis heart, to launch the preliminary model of the cybersecurity maturity mannequin on the coronary heart of the Cybersecurity Maturity Mannequin Certification (CMMC) program. CMMC supplies the DoD Workplace of the Beneath Secretary of Protection for Acquisition and Sustainment (OUSD(A&S)) with a robust device to enhance risk-informed choices and contractor safety within the protection industrial base provide chain.
SEI Influence on the Way forward for Software program Engineering Analysis
An vital a part of the SEI mission is to anticipate each challenges and alternatives in its three mission areas: software program engineering, cybersecurity, and AI. To develop an agenda for the following decade of software program engineering analysis, the SEI introduced collectively an advisory board of visionaries and senior thought leaders to develop an agenda for the following decade of software program engineering analysis. This effort led to the 2021 publication, Architecting the Way forward for Software program Engineering: A Nationwide Agenda for Software program Engineering Analysis and Improvement. The examine is a catalyst for analysis and improvement at Carnegie Mellon College and the SEI in areas similar to AI-augmented software program improvement, the assurance of constantly evolving software program techniques, and engineering AI-enabled software program techniques.
That SEI-led examine is influencing the DoD software program ecosystem and frightening follow-on actions. As an example, in 2023 the SEI and the Networking and Info Expertise Analysis and Improvement (NITRD) program organized and hosted the U.S. Management in Software program Engineering and AI Engineering workshop; see the workshop’s government abstract. As well as, we labored with the Nationwide Protection Industrial Affiliation’s Rising Applied sciences Institute (NDIA ETI) to supply suggestions for the DoD because it shapes its software program modernization actions and analysis portfolio. Additional, the SEI is partnering with the software program engineering and AI communities to implement the suggestions of the analysis agenda. The SEI partnered with the Federal Aviation Administration and Vanderbilt College to convene two workshops in 2024 to deal with the reassurance of constantly evolving software program techniques, one of many examine’s areas of focus. SEI researchers together with leaders from the software program engineering neighborhood can be main a workshop to deal with how AI may remodel end-to-end software program improvement workflows within the 2025 Worldwide Workshop on Envisioning the AI-Augmented Software program Improvement Lifecycle, collocated with the ACM Worldwide Convention on the Foundations on Software program Engineering.
The SEI: Persistent Deal with Software program Modernization
By way of the SEI Weblog and our podcast collection, we spotlight the work of our researchers to assist the DoD make software program a strategic benefit by way of integrating our area experience in AI, cybersecurity, and software program. To assist the DoD ship resilient software program functionality on the velocity of relevance, the SEI researches complicated engineering issues; creates, prototypes, and refines progressive applied sciences; and transitions maturing options into follow to advertise DoD mission success.
