EMRGF: A Practitioner Framework for Governance-Driven Enterprise Technology Modernization

2026-05-11T08:51:47Z689c34a9f284d857208dc5c1448c639c0e8c277a7f642d66722b07f459ce2c56
AI-governanceCI/CDDBMS-adoptionEMRGFJavaLLM-agentsNISTScarfBenchSmellBenchagent-reliabilitybenchmarkscoding-agentsdeveloper-burnoutenterprise-governanceevaluationproactivityreproducibilityself-healingsoftware-migration

What happened

A collection of software-engineering and AI-systems papers focused on governance, reliability, and empirical evaluation of LLM-enabled tools and large-scale modernization. Highlights: EMRGF — an enterprise modernization governance operating model aligned to NIST CSF 2.0 / NIST AI RMF and US executive orders, reporting empirical improvements (≈30% dev effort reduction, 35% fewer test cycles, zero-disruption migrations, 99.9% data reliability). Multiple empirical evaluations of agent and model behavior: the Single-File Test compares GPT/Gemini/Grok/Claude for public HTML generation (Claude best/

Why it matters

A reviewed impact interpretation has not been published for this record.

Evidence and limitations

Source ID
arxiv_cs_se
Record identifier
689c34a9f284d857208dc5c1448c639c0e8c277a7f642d66722b07f459ce2c56
Enrichment time
2026-05-11T08:51:47Z
AI-assisted enrichment
Yes

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