AI-Assisted Legacy Code Conversion for Developers
Employment & Work
What it collects
- Legacy source code written in older programming languages such as COBOL, Fortran, or older versions of Java or C#. This is software artefact data, not personal information.
- Run by
- National Defence (DND)
- Where
- No fixed location
- Kept
- Not stated by the Helpful Places.
- Shared with
- Not stated by the Helpful Places.
- Your copy
- You cannot see the data it holds about you. What you can do
What it is for
This system uses generative AI and natural language processing to automatically translate software written in older programming languages (such as COBOL or Fortran) into modern languages (such as Python, Java, or Go). It is intended for use by Government of Canada employees involved in software development and system modernization. The system does not process personal information. Users are not currently informed that AI is being used.
What it collects and what happens to it
Data taken in
- Legacy source code written in older programming languages such as COBOL, Fortran, or older versions of Java or C#. This is software artefact data, not personal information.
Processing
- The system applies large language models (LLMs) and NLP techniques to parse legacy programming language syntax and generate semantically equivalent code in the target language.
What it does
- The system uses generative AI to produce translated source code in a target modern programming language. A developer reviews and validates the generated output before adoption.
- The system uses NLP to understand the structure and semantics of legacy source code prior to translation.
Outputs
- Translated source code in a modern target programming language such as Python, Java, Go, or C#. The output is software code, not personal information.
Run by
- The Department of National Defence is deploying this AI-assisted code conversion tool for use by Government of Canada employees engaged in software modernization.
Built by
- The Government of Canada developed this system internally.
Kept for
Not stated by the Helpful Places.
Shared with
- This system processes government source code, not personal data. As a result, individual data-access rights are not applicable. The register does not describe any public-facing access mechanism for outputs.
Stored
Not stated by the Helpful Places.
How to read the colours
Can it identify you?
- Anonymized data
- Data about people with the link to who is broken. Stripped of identifiers, blurred, aggregated, or noised so this system can’t reasonably tie a record back to an individual.
- Pseudonymous data
- Each person’s data is tied to a token (hash, ID, template) that lets this system recognise the same person across events, but the token itself doesn’t reveal a name. Reidentification is possible with extra information.
- Identifiable data
- The data either contains a direct identifier (name, address, account name, recognisable face or voice, plate number) or carries a token this system uses to look up legal identity during processing.
Who completes the loop?
- Human decides
- This mode suggests; a person decides what to do next. The AI is always advisory — a human is in the loop on every decision. Example: a triage tool ranks cases for a clinician who chooses which to see first.
- Human executes
- This mode decides; a person carries out the result. Example: an optimizer plans the day’s trash-collection routes, and drivers run them.
- Autonomous
- This mode decides and acts on its own. No person reviews each decision or carries out the resulting action.
Definitions from the DTPR standard. Amber is about your data, violet about who decides. The fuller the shape and the deeper the colour, the more identifying the data or the less a person is involved.
- AI registerGovernment of Canada Algorithmic Impact Assessment Register — Code Conversion (2526-DND-MDN-002)National Defence, Government of Canada. AI Register ID: 2526-DND-MDN-002.
- AI registerGovernment of Canada AI Register — Code Conversion
- AI registerGovernment of Canada AI Register — Code Conversion
- Register entryPublished by the Helpful Places. Reference 9165b752. This disclosure was drafted with AI assistance.Schema: ai@2026-05-06-beta
What you can do
Ask about this system
Questions go to the Helpful Places, not the vendor.
Your rights
- Right to Be Informed of AI UseThe register states that AI use is not currently disclosed to users. As of the date of this record, GC employees using this tool are not informed that AI is involved in the code conversion process.
Risks and safeguards
- Societal & cultural harmGenerated code may contain subtle logic errors, security vulnerabilities, or non-idiomatic translations that are difficult for reviewers to detect.Safeguard: The system is still in development; human review by developers before code adoption is the primary safeguard. No automated deployment of generated code without human validation is described in the register.