> ## Documentation Index > Fetch the complete documentation index at: https://docs.generalvalidation.com/llms.txt > Use this file to discover all available pages before exploring further. # Tests > The twelve validation functions, how each comparison behaves, and how to add, edit, and delete a Test on a Table Pair. A Test applies one function to a Table Pair and reports whether the source and target agree. Tests belong to a Table Pair, share its join keys and filters, and compare outcomes; they do not reproduce your transformation. This page describes the twelve functions, how comparisons behave, and how to manage Tests. For pairing Tables, see [Create Table Pairs](/creating-your-first-test); for running Tests, see [Runs, Results, and evidence](/runs-results-and-evidence). ## The 12 validation functions Each Test applies one function to the Table Pair. Every function except `COUNT_ROWS` maps one source column to one target column, and each Test is labeled by its function code. Filters on the Table Pair apply to every Test in it. Aggregate comparisons reduce each side to one number and compare the two. They accept an absolute threshold. | Code | What it compares | Needs | | ---------------- | ------------------------------------------------------------------------- | ------------------------------------------ | | `COUNT_ROWS` | The total number of rows in the source and in the target. | No column mapping. | | `COUNT` | The number of non-null values in the mapped columns. | A source column and a target column. | | `COUNT_DISTINCT` | The number of distinct non-null values in the mapped columns. | A source column and a target column. | | `MIN` | The smallest non-null value in each mapped column. | A source column and a target column. | | `MAX` | The largest non-null value in each mapped column. | A source column and a target column. | | `AVG` | The arithmetic mean of the non-null numeric values in each mapped column. | A numeric source column and target column. | | `SUM` | The sum of the non-null numeric values in each mapped column. | A numeric source column and target column. | Row comparisons match rows across the two Tables by join key and compare the mapped value row by row. They accept an absolute threshold, **Max bad records, and an Evidence limit**, and they need join keys on the Table Pair. Until the pair has join keys, the Add Test dialog asks you to set them in the Table Pair's settings first. | Code | What it compares | Needs | | ------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------ | | `VALUE` | The mapped values of rows whose join keys are present on both sides. Rows without a match on the other side are not compared. A pair with no common keys fails. | A source column, a target column, and join keys on the Table Pair. | | `OUTER_VALUE` | The mapped values across both key sets. A row present on only one side is a mismatch, even when the value on the other side would be null. | A source column, a target column, and join keys on the Table Pair. | Set comparisons collect the distinct values of the mapped column on each side and compare the two sets. They have no threshold, and they accept Max bad records and an Evidence limit. | Code | What it compares | Needs | | ---------------- | ------------------------------------------------------------- | ------------------------------------ | | `SET_A_IN_B` | Whether every distinct source value is present in the target. | A source column and a target column. | | `SET_B_IN_A` | Whether every distinct target value is present in the source. | A source column and a target column. | | `SET_A_EQUALS_B` | Whether the two distinct value sets are equal. | A source column and a target column. | Pair a `VALUE` Test with `COUNT_ROWS` or `OUTER_VALUE` when unmatched rows matter. ## How comparisons behave Verdicts. A Test either passes, fails, or errors. It passes when the two sides agree within its threshold or allowance, and fails when they do not. It errors when the comparison could not run: Could not read the Tables means a source or target could not be read, The Test could not finish means a mapped column is missing, the function cannot be applied to the column's type, or a value could not be cast, and Could not save Result details means the mismatch evidence could not be written. A read failure on either Table marks every Test in the Run as an error. Each Result shows how many comparisons, rows, or values were compared and how many mismatched. Nulls. Value comparisons use null-safe equality: a null on both sides is a match. Two null aggregate outputs compare equal. Sets treat null as one distinct member and ignore how many times a value appears. `COUNT`, `COUNT_DISTINCT`, `MIN`, `MAX`, `AVG`, and `SUM` count or compute only non-null values. Join keys. Join keys follow ordinary join semantics, including for duplicate and null key values. A key value that appears on more than one row multiplies the matches, so choose keys that identify each row once. `VALUE` fails with the reason No matching join keys when the keys produce no common rows. `OUTER_VALUE` treats a row missing from either side as a mismatch. Empty inputs. When a side has no rows, or every value in the mapped column is null, `MIN`, `MAX`, `AVG`, and `SUM` produce null and counts produce zero. Because two null aggregates compare equal, two empty inputs pass an aggregate Test. `OUTER_VALUE` on two empty inputs passes; `VALUE` on two empty inputs fails because there are no common keys. Absolute threshold. Numeric aggregates and row comparisons pass when the absolute difference between the two values is within the threshold. The default is 0, which requires exact equality; the field says **Use 0 for exact equality.** The threshold is an absolute amount, not a percentage. Count Tests can allow an absolute difference in counts; distinct counts are computed exactly. Set Tests have no threshold. Max bad records. For row and set Tests, Max bad records (default 0) lets that many mismatches remain and still pass. A Test that passes this way shows the reason Within allowed bad records, and its mismatch count stays exact. The allowance never excuses an error or a `VALUE` Test with no common keys. Evidence limit. For row and set Tests, Evidence limit caps how many mismatched rows the Run saves to your Results Lakehouse. The default is 100, the maximum is 10,000, and 0 turns capture off. The limit changes only how much evidence is saved; it never changes the verdict or the mismatch count. The app previews up to 100 of the saved rows; open the Results Lakehouse in Fabric to see all of them. See [Runs, Results, and evidence](/runs-results-and-evidence). ## Add a Test 1. On Table Pairs, click the pair's name to open it, then click **Add Test**. 2. Choose a Test function. The twelve functions are listed by code, from `COUNT_ROWS` to `SET_A_EQUALS_B`; their comparisons are described under [The 12 validation functions](#the-12-validation-functions). 3. Choose a Source column and a Target column. The dialog reads the column names and types live from the Tables and does not save them. Columns reflect the current Tables even when the pair pins an earlier Delta version. `COUNT_ROWS` compares total row counts and has no column fields. 4. Set the Absolute threshold. It defaults to 0, which requires exact equality, and it must be 0 or greater and at most 1e15. Set Tests have no threshold field. How the threshold applies to each function is described under [How comparisons behave](#how-comparisons-behave). 5. For `VALUE`, `OUTER_VALUE`, and the set Tests, set Max bad records and Evidence limit, described below. 6. Click **Add Test**. Max bad records (default 0) is the number of mismatches a row or set Test may have and still pass. Evidence limit (default 100, maximum 10,000) caps how many mismatched rows the Run saves as evidence in your Results Lakehouse; 0 turns evidence capture off, and the limit never changes the verdict or the mismatch count. How both settings affect a Result is described under [How comparisons behave](#how-comparisons-behave). The saved Test is labeled with its function code, such as `SUM`, and appears in the pair's Tests list with its columns, threshold, max bad records, and evidence setting. Its Latest Result shows Not run until a Run gives it a Result. Once the pair has at least one Test and the Environment is set up, Run validation on the pair's page submits a Run; see [Runs, Results, and evidence](/runs-results-and-evidence). ## Edit and delete a Test Each Test row has a ⋯ menu, on the pair's page and on Tests, with Edit Test and Delete Test. * Edit Test opens the same dialog as Add Test. Change the settings and click **Save Test**. Past Runs and their Results are unchanged: every Run keeps the definition it executed. The edited Test shows Not run until the new definition has a Result. * Delete Test asks for confirmation and removes the Test from the pair. Past Runs and Results remain available. ## Limits | Limit | Value | | ------------------------------------ | ------------------------- | | Tests per Table Pair | Up to 100 | | Absolute threshold | 0 to 1e15 | | Evidence limit | 0 to 10,000 rows per Test | | Mismatched rows previewed in the app | Up to 100 | Owners and Contributors add, edit, and delete Tests; Readers see the Tests of each Table Pair without the row menus. Every active Table Pair, with all of its Tests, counts as one Table Pair toward your plan; see [Plans and trial](/licensing-and-activation).