ToolJovia
Data

CSV Functional Dependency Review

Find concrete original-record counterexamples to declared determinant-to-dependent field rules in supplied CSV data.

✓ Browser-local processing
Processed in this tab. Up to 100,000 characters unless this tool states a smaller limit.

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How to use CSV Functional Dependency Review

Review whether repeated lookup keys consistently identify the same declared attributes before treating a table as a trusted mapping. Multiple rules are tested without deduplicating away conflicts, and observed consistency remains separate from a universal database design claim.

  1. Enter input, named determinant/dependent column rules json.
  2. Choose the settings for csv functional dependency review, then run the tool.
  3. Review the result and any limitations before copying or downloading it.

Good to know

  • 2,000 rows, 200,000 CSV characters (50,000 per cell, 100 columns) and 20 named rules, each with 1–20 determinant/dependent columns. At most 50 witnesses per rule, 200 total and 600,000 planned tuple characters; all violations remain counted.
  • Exact supplied strings, not SQL NULL, collation or numeric equality. A clean finite dataset does not establish a universal dependency, candidate key, 3NF/BCNF or inferred schema. Omitted incomplete rows are explicitly counted.
  • Processing is local. Output is limited to 1,000,000 text characters unless a stricter file limit is stated.

Common questions

Can zero violations prove the database is normalized?

No. It shows only that your chosen dependencies have no counterexample in the supplied rows under the declared empty-cell policy. Database normal forms depend on domain constraints and keys, not merely a sample with no observed conflict.

Is this input sent to a server?

No. The application processes this input inside your browser tab and does not save it to persistent storage.

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