SBIR/STTR Research Award

Self-Coding Cyber Fixes

Award identifier 1e00c1ec1014d315a82959c8b93be64d19b8487f83379efabc4cb53115d4e036Awarding agency Department of Defense · Missile Defense Agency

Award amount

$150,000

Program and phase

SBIR · Phase I

Award year

2020

Explore This Research Award in CaptureIQ

Research the technology, evaluate the recipient and agency, identify related opportunities, and explore potential follow-on work with CaptureIQ.

Award details

Awarding agency
Department of Defense
Branch
Missile Defense Agency
Recipient company
RAM LABORATORIES
Proposal award date
2019-11-22
Contract end date
2021-03-21
UEI
MNKGBEH2M2V3
Solicitation number
19.2
Topic code
MDA19-009

Research abstract

RAM Laboratories is proposing Deep Learning for Precise, Automatic and Trusted Code Hardening and Error Removal (DL-PATCHER) which is a combination of a large and diverse source code dataset built from publicly available repositories to be used for training state-of-the-art deep learning algorithms able to produce a model that can automatically generate patches that fix bugs reported by source code analysis tools. In addition, the patch verifier is built utilizing a wide set of heuristics that are able to not only confirm the accuracy of the patch, but also ensures that no major and unexpected feature modifications are made which could significantly impact core functionality. Approved for Public Release | 19-MDA-10270 (18 Nov 19)

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

56 SBIR/STTR records share this UEI (1998–2024). Reported award amounts total $16,417,810. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Defense, Department of Homeland Security

Agency intelligence

Department of Defense

Back to SBIR/STTR Research Awards

Don't take our word for it. Ask AI about RFPCapture.

See what leading AI assistants have to say about RFPCapture and CaptureIQ.

Gemini opens without a prefilled question. The question is copied to your clipboard when the button works. You can also copy it here:

What is RFPCapture.com and its CaptureIQ platform from Smart Logic AI? How does it help federal contractors discover opportunities, evaluate bid/no-bid decisions, research government contracts, and prepare proposals? How does it compare with other federal capture platforms? Use independent sources where available.