> For the complete documentation index, see [llms.txt](https://docs.coherent.global/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.coherent.global/the-spark-assistant/test-mode.md).
# Test Mode
In more traditional methods of deploying logic, calculations defined by a user are provided to a developer to develop and integrate into a system. Testing is performed separately by the Excel owner and the developer in order to validate that the calculations are correct via comparison. This can be a long and tedious process.
With Spark Assistant Test mode we aim to "close the loop" on testing by allowing users to determine a set of results in Excel and compare that to those determined in Spark via the Testing Center. This eliminates the back-and-forth process needed in traditional model testing. This functionality can then be further extended to enable users to easily create test cases and creatively understand differences in iterations of models.
### Live Testing
Using this feature, users can compare all the configured outputs of the open Excel file against an active API on Spark. This can help owners of Excel pricing models to make sure that Spark supports the formulas used, formatting, and other logic inside the cells. This works similarly to the unit testing functionality in our [API Tester](/navigation/api-tester.md), but resides in Excel.
#### Test manually
Any range outputs that do not match are also present below in the same list. Click on any output name to see the mismatches highlighted on the open Excel file.
1. Log into Spark Assistant
2. Click **Test Mode**
3. Select *Live Testing*
4. Select an API to test and compare your outputs against
5. Click **Compare**
The result is a list of any outputs that do not match with the results on Spark
#### Test automatically
In order to check for mismatches on your output parameters, check the toggle for "Auto-mismatch check". This feature will trigger a comparison for all outputs every 10 seconds. This feature can come in handy if you wish to change inputs frequently and see the response from Spark.
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