*   <li>{@link org.apache.maven.cling.invoker.mvnup.goals.PluginUpgradeStrategy} - Upgrades plugin versions for Maven 4 compatibility</li>
 *   <li>{@link org.apache.maven.cling.invoker.mvnup.goals.InferenceStrategy} - Applies Maven 4.1.0+ inference optimizations</li>
 *   <li>{@link org.apache.maven.cling.invoker.mvnup.goals.CompatibilityFixStrategy} - Fixes Maven 4 compatibility issues</li>
 * </ul>
 *
 * <h3>Utility Classes</h3>
 * <ul>

  private val provider: Provider =
    org.openjsse.net.ssl
      .OpenJSSE()

  // Selects TLSv1.3 so we are specific about our intended version ranges (not just 1.3)
  // and because it's a common pattern for VMs to have differences between supported and
  // defaulted versions for TLS based on what is requested.
  override fun newSSLContext(): SSLContext = SSLContext.getInstance("TLSv1.3", provider)

        }
    }

    @Nested
    @DisplayName("Inference Eligibility")
    class InferenceEligibilityTests {

        @ParameterizedTest(name = "for model version {0}")
        @ValueSource(strings = {"4.0.0", "4.1.0"})
        @DisplayName("should determine inference eligibility correctly")
        void shouldDetermineInferenceEligibilityCorrectly(String modelVersion) {

func (v *Value) InferBytesType() (err error) {
	b, ok := v.ToBytes()
	if !ok {
		return fmt.Errorf("InferByteType: Input is not bytes, but %v", v.GetTypeString())
	}

	// Check for numeric inference
	if x, ok := v.bytesToInt(); ok {
		v.setInt(x)
		return nil
	}
	if x, ok := v.bytesToFloat(); ok {
		v.setFloat(x)
		return nil
	}
	if x, ok := v.bytesToBool(); ok {
		v.setBool(x)

 * class was added for Java 8. The two classes are extremely similar, but incompatible (they cannot
 * share a common supertype). <i>All</i> known differences are listed either here or with the
 * relevant methods below.
 *
 * <ul>
 *   <li>This class is serializable; {@code java.util.Optional} is not.

    public static Set<Coordinates> computeAllArtifactCoordinates(UpgradeContext context, Map<Path, Document> pomMap) {
        Set<Coordinates> coordinates = new HashSet<>();

        context.info("Computing artifacts for inference from " + pomMap.size() + " POM(s)...");

        // Extract artifact from all POMs in the project
        for (Map.Entry<Path, Document> entry : pomMap.entrySet()) {
            Path pomPath = entry.getKey();

    assertThat(graph).isNotEqualTo(g2);
  }

  // Node/edge sets and node/edge connections are the same, but graph properties differ.
  // In this case the graphs are considered equivalent; the property differences are irrelevant.
  @Test
  public void equivalent_propertiesDiffer() {
    graph.putEdge(N1, N2);

    MutableGraph<Integer> g2 =
        GraphBuilder.from(graph).allowsSelfLoops(!graph.allowsSelfLoops()).build();

// `shape_inference::InferenceContext` constructor. Note the following:
//   - The inputs of the `op` are not used for shape inference. So, it is
//     OK to not have the inputs properly set in `op`. See `input_tensors`
//     if you want shape inference to consider the input tensors of the
//     op for shape inference.
//   - The types need not be set in `input_shapes` as it is not used.

    // We define the arithmetic means X_n = 1/n \sum_{i=1}^n x_i, and Y_n = 1/n \sum_{i=1}^n y_i.
    // We also define the sum of the products of the differences from the means
    //           C_n = \sum_{i=1}^n x_i y_i - n X_n Y_n
    // for all n >= 1. Then for all n > 1:
    //       C_{n-1} = \sum_{i=1}^{n-1} x_i y_i - (n-1) X_{n-1} Y_{n-1}

```
(You can paste links or attach files by dragging & dropping them below)
- Provide links to your updated versions of the above two colab notebooks.