# Knowledge-based test creation

While we expect everyone to use our automated Production test creation capabilities, we also recognize that many users bring significant expertise to their testing experience.  Distributional provides you a suite of test creation tools and patterns that match your needs.

Most tests in dbnl are statistically-motivated to better measure and study fundamentally nondeterministic AI-powered apps.  Means, percentiles, Kolmogorov-Smirnov, and other statistical entities are provided to allow you to study the behavior of your app as you would like.  We provide templates to guide you through our [suggested testing strategies](https://docs.dbnl.com/v0.25.x/to-be-deleted/testing-strategies).

<div align="center" data-full-width="false"><figure><img src="https://content.gitbook.com/content/RJtpFEsLhAXLBZsTPqF2/blobs/ElpTtO0QW4K40YtnGUG2/Screenshot%202024-11-19%20at%203.08.31%E2%80%AFPM.png" alt="" width="195"><figcaption><p>Menu of common testing strategies that are supported by templates in dbnl.</p></figcaption></figure></div>

The manual test creation process can be configured in any of three locations: in the main web UI test configuration page, through [shortcuts to the test drawer](https://docs.dbnl.com/v0.25.x/using-distributional/tests/creating-tests#context-driven-test-creation) scattered throughout the web UI, or through the SDK.  This gives you the flexibility to systematically control test generation, or quickly respond to insights for which you would like to test in the future.

The core testing capability is supplemented by the ability to define [filters on tests](https://docs.dbnl.com/v0.25.x/using-distributional/tests/creating-tests/using-filters-in-tests).  These filters empower you to test for consistency within subsets of your user base.  Filtering also allows you to test for bias in your app and help triage cases of undesired behavior.

Learn more about how to create your own tests [here](https://docs.dbnl.com/v0.25.x/using-distributional/tests/creating-tests).
