We make changes to Guava's public [APIs][], including adding new APIs, very
carefully. Because of this, if you're interested in seeing a new feature in
Guava, the best approach is to create an [issue][] (or comment on an existing
issue if there is one) requesting the feature and describing specific use cases
for it.

If the feature has merit, it will go through a thorough process of API design
and review. Any code should come after this.

* Create integration tests that exercise a Gradle build for the bug/feature. 
* Annotate tests that correspond to a bug on GitHub (`@Issue("https://github.com/gradle/gradle/issues/2622")`).
* Add documentation to the User Manual and DSL Reference (under [platforms/documentation/docs/src/docs](platforms/documentation/docs/src/docs/)).

*   When you contribute a new feature to TensorFlow, the maintenance burden is
    (by default) transferred to the TensorFlow team. This means that the benefit
    of the contribution must be compared against the cost of maintaining the
    feature.
*   Full new features (e.g., a new op implementing a cutting-edge algorithm)
    typically will live in