Abstract
The migration of database code may result in data corruption when static translation tools do not fully account for behavioral differences between source and target platforms, for example, in rounding or null value handling. A dynamic verification approach can address this. A system may passively observe a legacy database to capture truth vectors, which can be records linking transaction inputs to their verified outputs. Translated code can then be executed in an isolated sandbox environment using these inputs. A semantic comparator may analyze the new output against the legacy output from the truth vector. If a material discrepancy is found, a generative agent can receive contextual feedback and attempt to refine the translated code. This iterative cycle of executing, comparing, and remediating may continue to facilitate achieving behavioral equivalence, which can help mitigate hidden logical errors.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Rekhi, Khushmeet, "System for Autonomous Behavioral Verification and Remediation of Migrated Database Code", Technical Disclosure Commons, (January 18, 2026)
https://www.tdcommons.org/dpubs_series/9193