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pith:2026:LOONUOBW5MYO435TEP2ZCTPVBM
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AgentModernize: Preserving Business Logic in Legacy Modernization with Multi-Agent LLMs and Behavioral Specification Graphs

Marnim Galib, Sheikh Nazib Ahmed

A multi-agent framework with an explicit behavioral graph preserves business logic during legacy modernization where direct LLM translation loses it.

arxiv:2605.17535 v1 · 2026-05-17 · cs.SE

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Claims

C1strongest claim

Full AgentModernize with feedback was the only configuration with non-zero mean BER under every backbone. SP-LLM and CoT-LLM scored 0.0% on every scenario, on every backbone. The BSG captures 91.2% of gold-standard rules, confirming that the bottleneck is code generation, not extraction.

C2weakest assumption

The gold-standard tests used in the LegacyModernize-8 evaluation comprehensively cover all implicit business logic, edge cases, and cross-module constraints present in the original legacy systems (evaluation section).

C3one line summary

A multi-agent LLM framework with Behavioral Specification Graphs preserves business logic in legacy modernization, achieving non-zero mean BER on all tested scenarios where baseline LLM approaches scored zero.

References

26 extracted · 26 resolved · 4 Pith anchors

[1] A survey of legacy system modernization approaches, 2000
[2] A systematic review of software architecture evolution research, 2012 · doi:10.1016/j.infsof.2011.08.002
[3] Requirements for integrating software architecture and reengineering models: CORUM II, 1998 · doi:10.1109/wcre.1998.723185
[4] Model-driven reverse engi- neering, 2004 · doi:10.1109/ms.2004.23
[5] Evaluating Large Language Models Trained on Code 2021 · arXiv:2107.03374
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First computed 2026-05-20T00:04:44.496925Z
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Signature Pith Ed25519 (pith-v1-2026-05) · public key
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Canonical hash

5b9cda3836eb30ee6fb323f5914df50b057d0b1702bb2509250717572918082a

Aliases

arxiv: 2605.17535 · arxiv_version: 2605.17535v1 · doi: 10.48550/arxiv.2605.17535 · pith_short_12: LOONUOBW5MYO · pith_short_16: LOONUOBW5MYO435T · pith_short_8: LOONUOBW
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/LOONUOBW5MYO435TEP2ZCTPVBM \
  | 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: 5b9cda3836eb30ee6fb323f5914df50b057d0b1702bb2509250717572918082a
Canonical record JSON
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