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The Ultimate Code Review Checklist for Data Validation Frameworks

Shell QA 2026年08月17日 02:24 5 次阅读 来源:Dev.to

A comprehensive, production-ready checklist for reviewing data validation, ETL testing, and automated reconciliation codebases. Code reviews for data engineering tools need more rigor than standard web apps. A subtle bug in a data validation framework can cause silent pipeline failures, false positive test passes, or accidental execution of unbounded SQL queries on production warehouses. Whether you are building a custom data framework or maintaining automated ETL tests, use this generalized checklist during code reviews to keep your test suites secure, performant, and reliable. 1. Test Case Configuration (YAML / JSON) TC ID Matching: Ensure the tc_id value matches the configuration filename exactly. Schema Validity: Verify that type (e.g., count, data, recon, file) and source/target drivers are valid and supported. Explicit Enablers: Confirm the enabled field is explicitly set (true or false) rather than omitted. Relative File Paths: For file-based validation, ensure paths are relative to defined source/target data directories. Non-Empty Queries: Confirm SQL sources and targets include non-empty query strings or valid template paths. Unique Case IDs: Ensure test case identifiers are unique across the test suite directory. Documented Rationale: If a test case has enabled: false or uses numeric tolerance thresholds (validation_tolerance), ensure a comment explains the business reason. Dependency Order: Verify that basic structural checks (COUNT) run prior to deep comparisons (DATA / RECON). 2. SQL & Query Logic Explicit Projections: No SELECT *. All columns must be explicitly listed to avoid schema drift breaks. Alignment: Source and target queries must return compatible data types and matching column ordering. Environment Isolation: Check that query strings contain zero hardcoded hostnames, schema names, or environment paths. Secret Hygiene: Ensure queries contain no hardcoded credentials or connection strings. Warehouse Pushdown: Confirm filtering and heavy aggrega

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