given:
        def gradleVersion = GradleVersion.version("9.2")
        def allVersions = [
            "8.8.0", "8.9.0",
            "9.0.0-alpha01", "9.0.0-beta01", "9.0.0-rc01"
        ].shuffled()

        when:
        def selected = UpdateAgpVersions.selectVersionsFrom(gradleVersion, null, allVersions)

        then:
        selected == ["8.9.0", "9.0.0-rc01"]
    }

func shuffleWithDist[T any](input []T, distribution []int) []T {
	if distribution == nil {
		return input
	}
	shuffled := make([]T, len(input))
	for index := range input {
		blockIndex := distribution[index]
		shuffled[blockIndex-1] = input[index]
	}
	return shuffled
}

// Return shuffled partsMetadata depending on distribution.
func shufflePartsMetadata(partsMetadata []FileInfo, distribution []int) []FileInfo {

            EndpointPair.ordered(1, 2))
        .inOrder();
  }

  /**
   * Populates the graph with nodes and edges in a star shape with node `1` in the middle.
   *
   * <p>Note that the edges are added in a shuffled order to properly test the effect of the
   * insertion order.
   */
  private void populateStarShapedGraph() {
    putEdge(2, 1);
    putEdge(1, 4);
    putEdge(1, 3);
    putEdge(5, 1);

	if err != nil {
		removeRoots(disks)
		t.Fatal(err)
	}
	defer removeRoots(disks)
	z := objLayer.(*erasureServerPools)
	testShuffleDisks(t, z)
}

// Test shuffleDisks which returns shuffled slice of disks for their actual distribution.
func testShuffleDisks(t *testing.T, z *erasureServerPools) {
	disks := z.serverPools[0].GetDisks(0)()
	distribution := []int{16, 14, 12, 10, 8, 6, 4, 2, 1, 3, 5, 7, 9, 11, 13, 15}

        .inOrder();
  }

  /**
   * Populates the graph with nodes and edges in a star shape with node `1` in the middle.
   *
   * <p>Note that the edges are added in a shuffled order to properly test the effect of the
   * insertion order.
   */
  private void populateTShapedGraph() {
    putEdge(2, 1);
    putEdge(1, 4);
    putEdge(1, 3);
    putEdge(1, 2); // Duplicate

        .inOrder();
  }

  /**
   * Populates the graph with nodes and edges in a star shape with node `1` in the middle.
   *
   * <p>Note that the edges are added in a shuffled order to properly test the effect of the
   * insertion order.
   */
  private void populateTShapedGraph() {
    putEdge(2, 1);
    putEdge(1, 4);
    putEdge(1, 3);
    putEdge(1, 2); // Duplicate

      assertThat(graph.edges()).isEmpty(); // no edges can remain if there's no nodes
      AbstractGraphTest.validateGraph(graph);

      Collections.shuffle(nodeList, gen);
      for (Integer node : nodeList) {
        assertThat(graph.addNode(node)).isTrue();
      }
      Collections.shuffle(edgeList, gen);
      for (EndpointPair<Integer> edge : edgeList) {
        assertThat(graph.putEdge(edge.nodeU(), edge.nodeV())).isTrue();
      }

    *   `tf.data.Dataset.zip` now supports Python-style zipping, i.e. `Dataset.zip(a, b, c)`.
    * `tf.data.Dataset.shuffle` now supports `tf.data.UNKNOWN_CARDINALITY` When doing a "full shuffle" using  `dataset = dataset.shuffle(dataset.cardinality())`. But remember, a "full shuffle" will load the full dataset into memory so that it can be shuffled, so make sure to only use this with small datasets or datasets of small objects (like filenames).

*   `tf.math`

      AbstractNetworkTest.validateNetwork(network);

      Collections.shuffle(nodeList, gen);
      for (Integer node : nodeList) {
        assertThat(network.addNode(node)).isTrue();
      }
      Collections.shuffle(edgeList, gen);
      for (Object edge : edgeList) {
        assertThat(
                network.addEdge(

      }
      List<Element> tmp = new ArrayList<>(elementsInSet);
      shuffle(tmp, random);
      queryList.addAll(tmp.subList(0, extras));
    }

    // now add bad queries
    while (queryList.size() < numQueries) {
      Element candidate = newElement();
      if (!elementsInSet.contains(candidate)) {
        queryList.add(candidate);
      }
    }
    shuffle(queryList, random);
    return queryList.toArray(new Element[0]);
  }