* serialize collections that are defined elsewhere.
 *
 * @author Jared Levy
 */
@GwtIncompatible
@J2ktIncompatible
final class Serialization {
  private Serialization() {}

  /**
   * Stores the contents of a map in an output stream, as part of serialization. It does not support
   * concurrent maps whose content may change while the method is running.
   *

 * serialize collections that are defined elsewhere.
 *
 * @author Jared Levy
 */
@GwtIncompatible
@J2ktIncompatible
final class Serialization {
  private Serialization() {}

  /**
   * Stores the contents of a map in an output stream, as part of serialization. It does not support
   * concurrent maps whose content may change while the method is running.
   *

## Status

- ACCEPTED on 2023-12-01

## Context

In Gradle we often need to serialize in-memory objects for caching, or to transmit them across process barriers, etc.
Java serialization is one way to implement this, however, despite its simplicity of implementation, it has several drawbacks:

- **Performance:**
Java's built-in serialization mechanism is often slower compared to other serialization solutions.

import com.esotericsoftware.kryo.serializers.MapSerializer;

/**
 * A serializer class for handling object serialization and deserialization.
 * <p>
 * This class provides serialization capabilities using different serializers,
 * currently supporting Kryo and JavaBin serialization formats. The serializer
 * type is determined by the crawler data serializer configuration.
 * </p>
 * <p>

import java.util.TreeMap;

import org.codelibs.fess.unit.UnitFessTestCase;
import org.junit.jupiter.api.Test;
import org.junit.jupiter.api.TestInfo;

/**
 * Test class for DataSerializer.
 * Tests serialization and deserialization with Kryo and JavaBin.
 */
public class DataSerializerTest extends UnitFessTestCase {

    private DataSerializer serializer;

    @Override

    * If you didn't use FastAPI and used Starlette directly (or another tool, like Sanic, Flask, Responder, etc) you would have to implement all the data validation and serialization yourself. So, your final application would still have the same overhead...

* **No documentation**: Why document your API when an LLM can figure it out? Auto-generated OpenAPI docs are *so* 2020.
* **No serialization**: Just pass the raw, unstructured data around. Serialization is for people who don't trust their LLMs.
* **Embrace modern AI coding practices**: Leave everything up to an LLM to decide. The model knows best. Always.

    return false;
  }

  // All callers of the constructor are restricted to <K extends Enum<K>>.
  @Override
  @J2ktIncompatible // serialization
  Object writeReplace() {
    return new EnumSerializedForm<>(delegate);
  }

  @J2ktIncompatible // serialization
  private void readObject(ObjectInputStream stream) throws InvalidObjectException {
    throw new InvalidObjectException("Use EnumSerializedForm");
  }

But as TypeScript data is not preserved after compilation to JavaScript, it cannot rely on the types to define validation, serialization and documentation at the same time. Due to this and some design decisions, to get validation, serialization and automatic schema generation, it's needed to add decorators in many places. So, it becomes quite verbose.

    "path": "platforms/core-configuration/base-services-groovy",
    "unitTests": true,
    "functionalTests": false,
    "crossVersionTests": false
  },
  {
    "name": "bean-serialization-services",
    "path": "platforms/core-configuration/bean-serialization-services",
    "unitTests": false,
    "functionalTests": false,
    "crossVersionTests": false
  },
  {
    "name": "build-cache",