Inconsistency in spelling conventions can lead to several issues:

* **Confusion for users and contributors**: Mixed spellings (e.g., "color" and "colour", "initialize" and "initialise") in the codebase create confusion about which variant to use
* **Harder code search and refactoring**: Searching for identifiers, method names, or documentation becomes more difficult when multiple spellings exist for the same concept

#### Merging pull requests ####

Due to Guava's nature as a subset of Google's internal codebase which is
automatically synced to the public GitHub repository, we are unable to merge
pull requests directly into the master branch. Instead, once a pull request is
ready for merging, we'll make the appropriate changes in the internal codebase
and, when the change is synced out, give the pull request author credit for the
commit.

of a plugin (tasks, extensions, domain objects).  The Provider API provides a consistent way to set conventions, wire related configuration together (extension <- domain object <- task) and avoid evaluation ordering problems.

The Gradle codebase has evolved over time and has a mixture of simple getter/setter methods, Provider API and things in between.  It can be hard to follow best practices because Gradle provided types are reused in unexpected ways and extended by third party plugins....

### Core Features
- **Per-context configuration**: No global state, each context encapsulates configuration
- **Authentication**: NTLM, Kerberos, SPNEGO unified subsystem
- **SLF4J Logging**: Comprehensive logging throughout the codebase
- **Resource Management**: AutoCloseable patterns for file handles and connections
- **Thread Safety**: Components support concurrent access
- **DFS Support**: Distributed File System resolution

# ADR-0008 - Use NullAway for null checking

## Status

- ACCEPTED on 2025-08-06

## Context

Our codebase uses `null` extensively to represent an absence of value or optionality of the argument.
We utilize nullness annotations in Java code and somewhat rely on IDE warnings to guide us.
However, the Java code we have is not fully annotated, which causes several consequences:
* IDE warnings can be misleading

* Startup and shutdown events.
* Test client built on HTTPX.
* **CORS**, GZip, Static Files, Streaming responses.
* **Session and Cookie** support.
* 100% test coverage.
* 100% type annotated codebase.

## Pydantic features { #pydantic-features }

**FastAPI** is fully compatible with (and based on) [**Pydantic**](https://docs.pydantic.dev/). So, any additional Pydantic code you have, will also work.

* **WebSocket** 지원.
* 프로세스 내 백그라운드 작업.
* 시작 및 종료 이벤트.
* HTTPX 기반 테스트 클라이언트.
* **CORS**, GZip, 정적 파일, 스트리밍 응답.
* **세션과 쿠키** 지원.
* 100% test coverage.
* 100% type annotated codebase.

## Pydantic 기능 { #pydantic-features }

**FastAPI**는 [**Pydantic**](https://docs.pydantic.dev/)과 완벽하게 호환되며(또한 이를 기반으로 합니다). 따라서 추가로 가지고 있는 Pydantic 코드도 모두 동작합니다.

* In-process background tasks.
* Startup and shutdown events.
* Test client built on HTTPX.
* CORS, GZip, Static Files, Streaming responses.
* Session and Cookie support.
* 100% test coverage.
* 100% type annotated codebase.
* Few hard dependencies.

Starlette is currently the fastest Python framework tested. Only surpassed by Uvicorn, which is not a framework, but a server.

                    }
                }
            }
        }
        return commonRoot;
    }

    /**
     * Writes a Document to a file using the same format as the existing codebase.
     */
    private void writePomToFile(Document document, Path filePath) throws Exception {
        Files.writeString(filePath, document.toXml());
    }

    /**

        -  It could also be a simple python or TF utility that you could easily copy over to your own codebase. In those case, just make it your own!
        -  If you believe it should definitely be a public Keras API, please open a feature request in keras GitHub repo.