}

// edgeEntropyScore computes the entropy value for a set of edges
// coming in or out of a node. Entropy (as defined in information
// theory) refers to the amount of information encoded by the set of
// edges. A set of edges that have a more interesting distribution of
// samples gets a higher score.
func edgeEntropyScore(n *Node, edges EdgeMap, self int64) float64 {
	score := float64(0)
	total := self

        List<MetadataGraphEdge> edges = getIncidentEdges(vTo);
        if (edges == null || edges.isEmpty()) {
            return null;
        }

        List<MetadataGraphEdge> res = new ArrayList<>(edges.size());

        for (MetadataGraphEdge e : edges) {
            if (e.getSource().equals(vFrom)) {
                res.add(e);
            }

    assertThat(graph.nodes()).containsExactly("A");
    assertThat(graph.edges()).isEmpty();
  }

  @Test
  public void immutableGraphBuilder_putEdgeFromNodes() {
    ImmutableGraph<String> graph =
        GraphBuilder.directed().<String>immutable().putEdge("A", "B").build();

    assertThat(graph.nodes()).containsExactly("A", "B");
    assertThat(graph.edges()).containsExactly(EndpointPair.ordered("A", "B"));
  }

  @Test

    assertThat(graph.nodes()).containsExactly("A");
    assertThat(graph.edges()).isEmpty();
  }

  @Test
  public void immutableGraphBuilder_putEdgeFromNodes() {
    ImmutableGraph<String> graph =
        GraphBuilder.directed().<String>immutable().putEdge("A", "B").build();

    assertThat(graph.nodes()).containsExactly("A", "B");
    assertThat(graph.edges()).containsExactly(EndpointPair.ordered("A", "B"));
  }

  @Test

  // * replace edges to "Enter" nodes, and edges from "Exit" nodes with edges
  //   to/from the corresponding frame node. In essence, we collapse the loop
  //   into a single node for the purpose of cycle detection in the enclosing
  //   graph.
  // * the body of the loop should now be disconnected from the rest of the
  //   graph; we make it acyclic by breaking loop backedges (edges outgoing from
  //   "NextIteration" nodes.

// These blocks were inserted to remove critical edges.
func trim(f *Func) {
	n := 0
	for _, b := range f.Blocks {
		if !trimmableBlock(b) {
			f.Blocks[n] = b
			n++
			continue
		}

		bPos := b.Pos
		bIsStmt := bPos.IsStmt() == src.PosIsStmt

		// Splice b out of the graph. NOTE: `mergePhi` depends on the
		// order, in which the predecessors edges are merged here.
		p, i := b.Preds[0].b, b.Preds[0].i

		var b bytes.Buffer
		g.TransitiveReduction()
		// Add cyclic edges for visualization.
		for k := range cyclicRanks {
			g.AddEdge(k, k)
		}
		// Reverse the graph. It's much easier to read this as
		// a "<" partial order than a ">" partial order. This
		// ways, locks are acquired from the top going down
		// and time moves forward over the edges instead of
		// backward.
		g.Transpose()
		generateDot(&b, g)

    assertThat(network.edges()).isEmpty();
  }

  @Test
  public void immutableNetworkBuilder_putEdgeFromNodes() {
    ImmutableNetwork<String, Integer> network =
        NetworkBuilder.directed().<String, Integer>immutable().addEdge("A", "B", 10).build();

    assertThat(network.nodes()).containsExactly("A", "B");
    assertThat(network.edges()).containsExactly(10);

            if (!s.ok()) {
              return;
            }
            node_map[n] = copy;
          }

          // Only handle input edges. Output edges will be added later as
          // its output nodes' input edges.
          for (auto e : n->in_edges()) {
            if (node_map.find(e->src()) == node_map.end()) {
              s = errors::Internal("Cannot find node image for ",

 */
@ElementTypesAreNonnullByDefault
abstract class AbstractDirectedNetworkConnections<N, E> implements NetworkConnections<N, E> {
  /** Keys are edges incoming to the origin node, values are the source node. */
  final Map<E, N> inEdgeMap;

  /** Keys are edges outgoing from the origin node, values are the target node. */
  final Map<E, N> outEdgeMap;

  private int selfLoopCount;