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Many businesses depend on legacy systems, which often use outdated technologythat complicates maintenance and updates. Therefore, software modernization isessential, particularly data migration between different database schemas.Established methodologies, like model transformation and ETL tools, facilitatethis migration; they require deep knowledge of database languages and both thesource and target schemas. This necessity renders data migration an error-proneand cognitively demanding task. Our objective is to alleviate developers'workloads during schema evolution through our DAMI-Framework. This frameworkincorporates a domain-specific language (DSL) and a parser to facilitate datamigration between database schemas. DAMI-DSL simplifies schema mapping whilethe parser automates SQL script generation. We assess developer experience indata migration by conducting an empirical evaluation with 21 developers toassess their experiences using our DSL versus traditional SQL. The study allowsus to measure their perceptions of the DSL properties and user experience. Theparticipants praised DAMI-DSL for its readability and ease of use. The findingsindicate that our DSL reduces data migration efforts compared to SQL scripts.

Seamless Data Migration between Database Schemas with DAMI-Framework: An Empirical Study on Developer Experience