* mentioned in the method Javadoc does in fact compile.
   */

  @SuppressWarnings("unused") // compilation test
  public void testSampleCodeError1() {
    Optional<Integer> optionalInt = getSomeOptionalInt();
    // Number value = optionalInt.or(0.5); // error
  }

  @SuppressWarnings("unused") // compilation test
  public void testSampleCodeError2() {
    FluentIterable<? extends Number> numbers = getSomeNumbers();

val codenarcVersion = if (isGroovy4) "3.1.0-groovy-4.0" else "3.1.0"
val spockVersion = if (isGroovy4) "2.2-groovy-4.0" else "2.2-groovy-3.0"
val asmVersion = "9.7"
// To try out better kotlin compilation avoidance and incremental compilation
// with -Pkotlin.incremental.useClasspathSnapshot=true
val kotlinVersion = providers.gradleProperty("buildKotlinVersion")
    .getOrElse(embeddedKotlinVersion)

dependencies {
    constraints {

     *
     * @throws MojoExecutionException if an unexpected problem occurs.
     * Throwing this exception causes a "BUILD ERROR" message to be displayed.
     * @throws MojoFailureException if an expected problem (such as a compilation failure) occurs.
     * Throwing this exception causes a "BUILD FAILURE" message to be displayed.
     */
    void execute() throws MojoExecutionException, MojoFailureException;

    /**

 * specific language governing permissions and limitations
 * under the License.
 */
package org.apache.maven.plugin;

/**
 * An exception occurring during the execution of a plugin (such as a compilation failure).<br>
 * Throwing this exception causes a "BUILD FAILURE" message to be displayed.
 *
 */
public class MojoFailureException extends AbstractMojoExecutionException {
    /**

should be used with caution when working with untrusted models.

### Saved graphs and checkpoints

When loading untrusted serialized computation graphs (in form of a `GraphDef`,
`SavedModel`, or equivalent on-disk format), the set of computation primitives
available to TensorFlow is powerful enough that you should assume that the
TensorFlow process effectively executes arbitrary code.

                    writer.write(newContent);
                }
            } catch (IOException e) {
                logError("Failed to write to file", e);
                throw e; // Re-throw to ensure the compilation fails
            }
        } else {
            logMessage(Diagnostic.Kind.NOTE, "Content unchanged. Skipping file update.");
        }
    }

    assertThat(min(2, 1, reverse)).isEqualTo(2);
    assertThat(max(1, 2, reverse)).isEqualTo(1);
    assertThat(max(2, 1, reverse)).isEqualTo(1);
  }

  /**
   * Fails compilation if the signature of min and max is changed to take {@code Comparator<T>}
   * instead of {@code Comparator<? super T>}.
   */
  public void testMinMaxWithSupertypeComparator() {

    "groups" : [ {
      "testProject" : "largeJavaMultiProject",
      "comment" : "We only test the multi-project here since for the monolithic project we would have no cache hits. This would mean we actually would test incremental compilation.",
      "coverage" : {
        "per_commit" : [ "linux" ]
      }
    } ]
  }, {

     * @return the list of compile source roots
     */
    @Nonnull
    List<Path> getCompileSourceRoots(@Nonnull Project project, @Nonnull ProjectScope scope);

    /**
     * Add a compilation source root to the given project for the given scope.
     * The path will be transformed into an absolute path and added to the list for the given scope,
     * if not already present.
     *

      True, ('Would you like to override eigen strong inline for some C++ '
             'compilation to reduce the compilation time?'),
      'Eigen strong inline overridden.', 'Not overriding eigen strong inline, '
      'some compilations could take more than 20 mins.'):
    # Due to a known MSVC compiler issue
    # https://github.com/tensorflow/tensorflow/issues/10521