*/
        return sqrtFloor + lessThanBranchFree(halfSquare, x);
      default:
        throw new AssertionError();
    }
  }

  private static int sqrtFloor(int x) {
    // There is no loss of precision in converting an int to a double, according to
    // http://java.sun.com/docs/books/jls/third_edition/html/conversions.html#5.1.2
    return (int) Math.sqrt(x);
  }

  /**

    assertThat(transformation.slope()).isWithin(ALLOWED_ERROR).of(slope);
    // Note that we cannot test the actual mapping of points, as the results will be unreliable due
    // to loss of precision with this value of the slope.
  }

  public void testMappingWithSlope_maximalSlope() {
    double x1 = 1.2;
    double y1 = 3.4;
    double slope = Double.MAX_VALUE;

    assertThat(transformation.slope()).isWithin(ALLOWED_ERROR).of(slope);
    // Note that we cannot test the actual mapping of points, as the results will be unreliable due
    // to loss of precision with this value of the slope.
  }

  public void testMappingWithSlope_maximalSlope() {
    double x1 = 1.2;
    double y1 = 3.4;
    double slope = Double.MAX_VALUE;

import java.util.Collections;
import java.util.List;
import junit.framework.Test;
import junit.framework.TestCase;
import junit.framework.TestResult;

/**
 * @author Max Ross
 */
public class FeatureSpecificTestSuiteBuilderTest extends TestCase {
  private static final class MyTestSuiteBuilder
      extends FeatureSpecificTestSuiteBuilder<MyTestSuiteBuilder, String> {

 *
 * <p>This class is intended as a replacement for {@link ReentrantLock}. Code using {@code Monitor}
 * is less error-prone and more readable than code using {@code ReentrantLock}, without significant
 * performance loss. {@code Monitor} even has the potential for performance gain by optimizing the
 * evaluation and signaling of conditions. Signaling is entirely <a

   *     cause loss of precision)
   */
  public void addAll(Iterable<? extends Number> values) {
    for (Number value : values) {
      add(value.doubleValue());
    }
  }

  /**
   * Adds the given values to the dataset.
   *
   * @param values a series of values, which will be converted to {@code double} values (this may
   *     cause loss of precision)
   */

    asByteSource(from).copyTo(to);
  }

  /**
   * Copies all the bytes from one file to another.
   *
   * <p>Copying is not an atomic operation - in the case of an I/O error, power loss, process
   * termination, or other problems, {@code to} may not be a complete copy of {@code from}. If you
   * need to guard against those conditions, you should employ other file-level synchronization.
   *

    this.max = max;
  }

  /**
   * Returns statistics over a dataset containing the given values.
   *
   * @param values a series of values, which will be converted to {@code double} values (this may
   *     cause loss of precision)
   */
  public static Stats of(Iterable<? extends Number> values) {
    StatsAccumulator accumulator = new StatsAccumulator();
    accumulator.addAll(values);
    return accumulator.snapshot();
  }

import java.util.Collections;
import java.util.List;
import junit.framework.Test;
import junit.framework.TestCase;
import junit.framework.TestResult;

/**
 * @author Max Ross
 */
public class FeatureSpecificTestSuiteBuilderTest extends TestCase {
  private static final class MyTestSuiteBuilder
      extends FeatureSpecificTestSuiteBuilder<MyTestSuiteBuilder, String> {

    // The upper bound on the length of an array and the bounds on the int values mean that, in
    // this case only, we can compute the sum as a long without risking overflow or loss of
    // precision. So we do that, as it's slightly quicker than the Knuth algorithm.
    long sum = 0;
    for (int index = 0; index < values.length; ++index) {
      sum += values[index];
    }