Harshavardhana <******@****.***> 1722276604 -0700

Klaus Post <******@****.***> 1700528975 -0800

	if err != nil {
		return err
	}
	sa.AddRunningKubeSourceWithRevision(k, revision, false)
	res, err := sa.Analyze(make(chan struct{}))
	if err != nil {
		return err
	}
	relevantMessages := diag.Messages{}
	for _, msg := range res.Messages.FilterOutLowerThan(diag.Error) {
		if msg.Resource.Metadata.FullName.Name == resource.LocalName(name) {

Klaus Post <******@****.***> 1700528975 -0800

  }

  @Benchmark
  int asciiStringToUpperCase(int reps) {
    String string = noWorkToDo ? Ascii.toUpperCase(testString) : testString;

    int dummy = 0;
    for (int i = 0; i < reps; i++) {
      dummy += Ascii.toUpperCase(string).length();
    }
    return dummy;
  }

  @Benchmark
  int asciiCharSequenceToUpperCase(int reps) {

  int hashString_4(int reps) {
    int dummy = 0;
    for (int i = 0; i < reps; i++) {
      dummy += Objects.hashCode(S0, S1, S2, S3);
    }
    return dummy;
  }

  @Benchmark
  int hashString_5(int reps) {
    int dummy = 0;
    for (int i = 0; i < reps; i++) {
      dummy += Objects.hashCode(S0, S1, S2, S3, S4);
    }
    return dummy;
  }

  @Benchmark
  int hashMixed_5(int reps) {
    int dummy = 0;

  @Benchmark
  int weakInterner(int reps) {
    Interner<String> interner = Interners.newWeakInterner();
    for (int i = 0; i < reps; i++) {
      String unused = interner.intern(Double.toHexString(Math.random()));
    }
    return reps;
  }

  @Benchmark
  int strongInterner(int reps) {
    Interner<String> interner = Interners.newStrongInterner();
    for (int i = 0; i < reps; i++) {

    return datasets[i & 0xFF].clone();
  }

  @Benchmark
  double median(int reps) {
    double dummy = 0.0;
    for (int i = 0; i < reps; i++) {
      dummy += algorithm.singleQuantile(1, 2, dataset(i));
    }
    return dummy;
  }

  @Benchmark
  double percentile90(int reps) {
    double dummy = 0.0;
    for (int i = 0; i < reps; i++) {
      dummy += algorithm.singleQuantile(90, 100, dataset(i));
    }

    return datasets[i & 0xFF].clone();
  }

  @Benchmark
  double median(int reps) {
    double dummy = 0.0;
    for (int i = 0; i < reps; i++) {
      dummy += algorithm.singleQuantile(1, 2, dataset(i));
    }
    return dummy;
  }

  @Benchmark
  double percentile90(int reps) {
    double dummy = 0.0;
    for (int i = 0; i < reps; i++) {
      dummy += algorithm.singleQuantile(90, 100, dataset(i));
    }

Harshavardhana <******@****.***> 1721816641 -0700