@Nonnull
    Map<ChecksumAlgorithm, String> calculate(@Nonnull byte[] data, @Nonnull Collection<ChecksumAlgorithm> algorithms);

    /**
     * Calculates checksums for specified data.
     *
     * @param data        The content for which to calculate checksums, must not be {@code null}.
     * @param algorithms  The checksum algorithms to use, must not be {@code null}.
     * @return The calculated checksums, indexed by algorithms, never {@code null}.

        testInheritance("no-append-urls3");
    }

    /**
     * Tricky case: flat directory structure, but child directory != artifactId.
     * Model interpolation does not give same result when calculated from build or from repo...
     * This is why MNG-5000 fix in code is marked as bad practice (uses file names)
     * @throws IOException Model read problem
     */
    @Test

	return "Bad sha256: Expected " + e.ExpectedSHA256 + " does not match calculated " + e.CalculatedSHA256
}

// BadDigest - Content-MD5 you specified did not match what we received.
type BadDigest struct {
	ExpectedMD5   string
	CalculatedMD5 string
}

func (e BadDigest) Error() string {
	return "Bad digest: Expected " + e.ExpectedMD5 + " does not match calculated " + e.CalculatedMD5
}

// SizeTooSmall reader size too small

## Decision

### Types of properties that should not use lazy types

The guidelines below do not apply to all properties. There are cases where the lazy types should not be used:

#### Non-calculated values

These are inappropriate uses of lazy types:

```groovy
class Example {
    Property<String> getSomeProperty()

    Example() {
        getSomeProperty().set("value")

						for idx, sh := range parityData {
							calculated := splitData[idx]
							if !bytes.Equal(calculated, sh) {
								off := 0
								for i, v := range sh {
									if v != calculated[i] {
										off = i
										break
									}
								}
								calculated := calculated[off:]
								inFile := sh[off:]
								extra := ""
								if len(calculated) != len(inFile) {

    /**
     * Specifies a single quantile index to be calculated, i.e. the k in the kth q-quantile.
     *
     * @param index the quantile index, which must be in the inclusive range [0, q] for q-quantiles
     */
    public ScaleAndIndex index(int index) {
      return new ScaleAndIndex(scale, index);
    }

    /**
     * Specifies multiple quantile indexes to be calculated, each index being the k in the kth
     * q-quantile.

  // update. Value can be an absolute number (ex: 5) or a percentage of total
  // number of DaemonSet pods at the start of the update (ex: 10%). Absolute
  // number is calculated from percentage by rounding up.
  // This cannot be 0 if MaxSurge is 0
  // Default value is 1.
  // Example: when this is set to 30%, at most 30% of the total number of nodes

      return LinearTransformation.vertical(xStats.mean());
    }
  }

  /**
   * {@inheritDoc}
   *
   * <p><b>Note:</b> This tests exact equality of the calculated statistics, including the floating
   * point values. Two instances are guaranteed to be considered equal if one is copied from the
   * other using {@code second = new PairedStatsAccumulator().addAll(first).snapshot()}, if both

     *
     * @return The base directory of the current project or {@code null} if none.
     */
    File getProjectDirectory();

    /**
     * Gets current calculated project properties
     *
     * @return The project properties, never {@code null}.
     */
    Map<String, String> getProjectProperties();

message RollingUpdateDeployment {
  // The maximum number of pods that can be unavailable during the update.
  // Value can be an absolute number (ex: 5) or a percentage of desired pods (ex: 10%).
  // Absolute number is calculated from percentage by rounding down.
  // This can not be 0 if MaxSurge is 0.
  // Defaults to 25%.
  // Example: when this is set to 30%, the old ReplicaSet can be scaled down to 70% of desired pods