Orchestrating Black-Box Schema Converters: An Empirical Study of Automated, Quality-Ranked Conversion Across Heterogeneous Schema Languages
arXiv 2606.26180•9810fb2174363974389488124a36fedb976710183af5f039743ec078910e3343
AI coding agentsConcoLixirDynFaultLLM oracleLLM-generated specificationsLLM-labelled codeSafety-Aware Mutation TestingSchema Conversion OrchestratorVeriFastaugmentation with dilutionautonomous drivingcode reviewconcolic testingdeep learning fault diagnosiseye trackinghuman contributorsmutation equivalencemutation testingopen sourceorchestrationquantum softwareschema conversionschema languagesseparation logictranspiler-based equivalence (TBE)
Paper metadata
- arXiv ID
- 2606.26180
- Version
- Not specified by this published record
- Category
- Computer Science — Software Engineering (cs.SE)
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Evidence and limitations
- Source ID
- arxiv_cs_se
- Record identifier
- 9810fb2174363974389488124a36fedb976710183af5f039743ec078910e3343
- Enrichment time
- 2026-06-26T08:51:53Z
- AI-assisted enrichment
- Yes
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