Artificial Intelligence (AI) Software Containerization

OUSD (R&E) CRITICAL TECHNOLOGY AREA(S): Advanced Computing and Software; The technology within this topic is restricted under the International Traffic in Arms Regulation (ITAR), 22 CFR Parts 120-130, which controls the export and import of defense-related material and services, including export of sensitive technical data, or the Export Administration Regulation (EAR), 15 CFR Parts 730-774, which controls dual use items. Offerors must disclose any proposed use of foreign nationals (FNs), their country(ies) of origin, the type of visa or work permit possessed, and the statement of work (SOW) tasks intended for accomplishment by the FN(s) in accordance with the Announcement. Offerors are advised foreign nationals proposed to perform on this topic may be restricted due to the technical data under US Export Control Laws. OBJECTIVE: Develop an AI/Machine Learning (ML) solution for auto containerizing existing Terminal High Altitude Area Defense (THAAD) software code. DESCRIPTION: The THAAD software is getting containerized and modularized as it is converted from ADA to C++. The desire of THAAD is to develop an AI/ML solution that could analyze the existing software and based upon the learning of the algorithm, then containerize the software code with minimal human intervention. PHASE I: Conduct an analysis of the possibility of being able to use AI/ML to perform auto-containerization of ADA and C++ software. PHASE II: Develop the algorithm to perform the analysis, perform training of the algorithm on non-tactical software code and then demonstrate the algorithm's ability to auto-containerize existing software code. PHASE III DUAL USE APPLICATIONS: Refine the algorithm and perform auto-containerization efforts on the existing ADA and C++ code. REFERENCES: 1. https://www.aptiv.com/en/insights/article/what-is-containerization 2. https://aws.amazon.com/blogs/apn/automating-containerization-at-scale-with-aws-app2container KEYWORDS: Containerization; Artificial Intelligence; Machine Learning