* R*R)} of the population standard deviation of {@code y}, where {@code R} is the Pearson's
   * correlation coefficient (as given by {@link #pearsonsCorrelationCoefficient()}).
   *
   * <p>The corresponding root-mean-square error in {@code x} as a function of {@code y} is a
   * fraction {@code sqrt(1/(R*R) - 1)} of the population standard deviation of {@code x}. This fit

/**
 * A decoded [mapping table] that can perform the [mapping step] of IDNA processing.
 *
 * This implementation is optimized for readability over efficiency.
 *
 * This implements non-transitional processing by preserving deviation characters.
 *
 * This implementation's STD3 rules are configured to `UseSTD3ASCIIRules=false`. This is
 * permissive and permits the `_` character.
 *

   * R*R)} of the population standard deviation of {@code y}, where {@code R} is the Pearson's
   * correlation coefficient (as given by {@link #pearsonsCorrelationCoefficient()}).
   *
   * <p>The corresponding root-mean-square error in {@code x} as a function of {@code y} is a
   * fraction {@code sqrt(1/(R*R) - 1)} of the population standard deviation of {@code x}. This fit

  /**
   * Returns the <a
   * href="http://en.wikipedia.org/wiki/Standard_deviation#Corrected_sample_standard_deviation">
   * corrected sample standard deviation</a> of the values. If this dataset is a sample drawn from a
   * population, this is an estimator of the population standard deviation of the population which
   * is less biased than {@link #populationStandardDeviation()} (the unbiased estimator depends on

   * R*R)} of the population standard deviation of {@code y}, where {@code R} is the Pearson's
   * correlation coefficient (as given by {@link #pearsonsCorrelationCoefficient()}).
   *
   * <p>The corresponding root-mean-square error in {@code x} as a function of {@code y} is a
   * fraction {@code sqrt(1/(R*R) - 1)} of the population standard deviation of {@code x}. This fit

  /**
   * Returns the <a
   * href="http://en.wikipedia.org/wiki/Standard_deviation#Corrected_sample_standard_deviation">
   * corrected sample standard deviation</a> of the values. If this dataset is a sample drawn from a
   * population, this is an estimator of the population standard deviation of the population which
   * is less biased than {@link #populationStandardDeviation()} (the unbiased estimator depends on

   * R*R)} of the population standard deviation of {@code y}, where {@code R} is the Pearson's
   * correlation coefficient (as given by {@link #pearsonsCorrelationCoefficient()}).
   *
   * <p>The corresponding root-mean-square error in {@code x} as a function of {@code y} is a
   * fraction {@code sqrt(1/(R*R) - 1)} of the population standard deviation of {@code x}. This fit

  // 4.1 Validate.

  // Must be NFC.
  if (decoded != normalizeNfc(decoded)) return null

  // TODO: Must not begin with a combining mark.
  // TODO: Each character must be 'valid' or 'deviation'. Not mapped.
  // TODO: CheckJoiners from IDNA 2008
  // TODO: CheckBidi from IDNA 2008, RFC 5893, Section 2.

  return Punycode.encode(decoded)

00DD          ; mapped                 ; 00FD          # 1.1  LATIN CAPITAL LETTER Y WITH ACUTE
00DE          ; mapped                 ; 00FE          # 1.1  LATIN CAPITAL LETTER THORN
00DF          ; deviation              ; 0073 0073     # 1.1  LATIN SMALL LETTER SHARP S
00E0..00F6    ; valid                                  # 1.1  LATIN SMALL LETTER A WITH GRAVE..LATIN SMALL LETTER O WITH DIAERESIS

//
// You should have received a copy of the GNU Affero General Public License
// along with this program.  If not, see <http://www.gnu.org/licenses/>.

// Package amztime implements AWS specific time parsing and deviations
package amztime

import (
	"errors"
	"testing"
	"time"
)

func TestParse(t *testing.T) {
	type testCase struct {
		expectedErr  error
		expectedTime time.Time
		timeStr      string
	}