due to design choices in Helm.
The underlying Kubernetes resources we configure have 1000s of fields; given enough users and bespoke use cases,
eventually someone will want to customize every one of those fields.
If all fields are exposed in `values.yaml`, we end up with an massive API that is also likely worse than just using the Kubernetes API directly.

      delegate.test();
    }
    return this;
  }

  private void testItems() {
    for (T item : items) {
      /*
       * TODO(cpovirk): consider no longer running these equivalent() tests on every Equivalence,
       * since the Equivalence base type now implements this logic itself
       */
      assertTrue(item + " must be inequivalent to null", !equivalence.equivalent(item, null));

name: Test

on:
  push:
    branches:
      - master
  pull_request:
    types:
      - opened
      - synchronize
  schedule:
    # cron every week on monday
    - cron: "0 0 * * 1"

jobs:
  lint:
    runs-on: ubuntu-latest
    steps:
      - name: Dump GitHub context
        env:
          GITHUB_CONTEXT: ${{ toJson(github) }}
        run: echo "$GITHUB_CONTEXT"
      - uses: actions/checkout@v4

   * for cross-language compatibility. For other use cases, prefer {@link #putUnencodedChars}, which
   * is faster, produces the same output across Java releases, and processes every {@code char} in
   * the input, even if some are invalid.
   */
  @CanIgnoreReturnValue
  PrimitiveSink putString(CharSequence charSequence, Charset charset);

          ImmutableSet.of(
              sun.misc.Unsafe.class.getName(), AtomicReferenceFieldUpdater.class.getName()));

  public static TestSuite suite() {
    // we create a test suite containing a test for every AbstractFutureTest test method and we
    // set it as the name of the test.  Then in runTest we can reflectively load and invoke the
    // corresponding method on AbstractFutureTest in the correct classloader.

		dataUsageJSON, err := json.Marshal(dataUsageInfo)
		if err != nil {
			scannerLogIf(ctx, err)
			continue
		}
		if attempts > 10 {
			saveConfig(ctx, objAPI, dataUsageObjNamePath+".bkp", dataUsageJSON) // Save a backup every 10th update.
			attempts = 1
		}
		if err = saveConfig(ctx, objAPI, dataUsageObjNamePath, dataUsageJSON); err != nil {
			scannerLogOnceIf(ctx, err, dataUsageObjNamePath)
		}
		attempts++
	}
}

  <!--
   | With toolchains you can refer to installations on your system. This
   | way you don't have to hardcode paths in your pom.xml.
   |
   | Every toolchain consist of 3 elements:
   | * type: the type of tool. An often used value is 'jdk'. Toolchains-aware
   |   plugins should document which type you must use.
   |
   | * provides: A list of key/value-pairs.

		prev.Count++
		l.IDMap[id] = prev
		shouldLog = false
	}
	l.Unlock()

	if shouldLog {
		logIf(ctx, subsystem, err, errKind...)
	}
}

// Cleanup the map every one hour so that the log message is printed again for the user to notice.
func (l *logOnceType) cleanupRoutine() {
	for {
		time.Sleep(time.Hour)

		l.Lock()
		l.IDMap = make(map[string]onceErr)
		l.Unlock()

   * the entry was returned by the iterator, except through the setValue operation on the map entry"
   * As such, this field must be cleared before every map mutation.
   *
   * Note about volatile: volatile doesn't make it safe to read from a mutable graph in one thread
   * while writing to it in another. All it does is help with _reading_ from multiple threads

              AtomicIntegerFieldUpdater.class.getName(),
              AtomicReferenceFieldUpdater.class.getName()));

  public static TestSuite suite() {
    // we create a test suite containing a test for every FuturesTest test method and we
    // set it as the name of the test.  Then in runTest we can reflectively load and invoke the
    // corresponding method on FuturesTest in the correct classloader.