pith:IVP2LCNR
Neural Code Translation of Legacy Code: APL to C#
Guided large language models translate APL legacy code to functional C# across program complexities
arxiv:2605.13896 v1 · 2026-05-12 · cs.SE · cs.PL
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\usepackage{pith}
\pithnumber{IVP2LCNRPD6ODXSHILT6TEQQ26}
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Record completeness
Claims
Our results demonstrate that neural code translation can successfully bridge the gap between APL and C# for a wide range of programs, and that incorporating additional context and guidance significantly improves model performance.
The constructed datasets of functionally equivalent APL-C# pairs are representative of real-world legacy code and that the automated pipeline of compilation plus execution testing reliably detects functional equivalence without false positives.
Guided LLM strategies with custom datasets and execution-based verification enable functional APL-to-C# translation across a range of program complexities.
References
Receipt and verification
| First computed | 2026-05-17T23:39:18.997182Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
455fa589b178fce1de4742e7e99210d7a248e1c960b44d0e129b84ed2e2d1151
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/IVP2LCNRPD6ODXSHILT6TEQQ26 \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 455fa589b178fce1de4742e7e99210d7a248e1c960b44d0e129b84ed2e2d1151
Canonical record JSON
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