DFS:

list nodes_to_visit = {root};
while( nodes_to_visit isn't empty ) {
  currentnode = nodes_to_visit.take_first();
  nodes_to_visit.prepend( currentnode.children );
  //do something
}

BFS:

list nodes_to_visit = {root};
while( nodes_to_visit isn't empty ) {
  currentnode = nodes_to_visit.take_first();
  nodes_to_visit.append( currentnode.children );
  //do something
}

两者的对称相当酷。

更新:如前所述，take_first()删除并返回列表中的第一个元素。

这是一个java程序的链接，显示DFS同时遵循递归和非递归方法，还计算发现和完成时间，但没有边对齐。

    public void DFSIterative() {
    Reset();
    Stack<Vertex> s = new Stack<>();
    for (Vertex v : vertices.values()) {
        if (!v.visited) {
            v.d = ++time;
            v.visited = true;
            s.push(v);
            while (!s.isEmpty()) {
                Vertex u = s.peek();
                s.pop();
                boolean bFinished = true;
                for (Vertex w : u.adj) {
                    if (!w.visited) {
                        w.visited = true;
                        w.d = ++time;
                        w.p = u;
                        s.push(w);
                        bFinished = false;
                        break;
                    }
                }
                if (bFinished) {
                    u.f = ++time;
                    if (u.p != null)
                        s.push(u.p);
                }
            }
        }
    }
}

这里是完整的源代码。

Stack<Node> stack = new Stack<>();
stack.add(root);
while (!stack.isEmpty()) {
    Node node = stack.pop();
    System.out.print(node.getData() + " ");

    Node right = node.getRight();
    if (right != null) {
        stack.push(right);
    }

    Node left = node.getLeft();
    if (left != null) {
        stack.push(left);
    }
}

如果你有指向父节点的指针，你可以在没有额外内存的情况下完成。

def dfs(root):
    node = root
    while True:
        visit(node)
        if node.first_child:
            node = node.first_child      # walk down
        else:
            while not node.next_sibling:
                if node is root:
                    return
                node = node.parent       # walk up ...
            node = node.next_sibling     # ... and right

注意，如果子节点存储为数组而不是通过兄弟指针，那么下一个兄弟节点可以通过以下方式找到:

def next_sibling(node):
    try:
        i =    node.parent.child_nodes.index(node)
        return node.parent.child_nodes[i+1]
    except (IndexError, AttributeError):
        return None

虽然“使用堆栈”可能是人为的面试问题的答案，但实际上，它只是显式地做递归程序在幕后所做的事情。

递归使用程序内置堆栈。当你调用一个函数时，它将函数的参数推入堆栈，当函数返回时，它通过弹出程序堆栈来执行。

基于biziclops的ES6实现很棒的答案:

root = { text: "root", children: [{ text: "c1", children: [{ text: "c11" }, { text: "c12" }] }, { text: "c2", children: [{ text: "c21" }, { text: "c22" }] }, ] } console.log("DFS:") DFS(root, node => node.children, node => console.log(node.text)); console.log("BFS:") BFS(root, node => node.children, node => console.log(node.text)); function BFS(root, getChildren, visit) { let nodesToVisit = [root]; while (nodesToVisit.length > 0) { const currentNode = nodesToVisit.shift(); nodesToVisit = [ ...nodesToVisit, ...(getChildren(currentNode) || []), ]; visit(currentNode); } } function DFS(root, getChildren, visit) { let nodesToVisit = [root]; while (nodesToVisit.length > 0) { const currentNode = nodesToVisit.shift(); nodesToVisit = [ ...(getChildren(currentNode) || []), ...nodesToVisit, ]; visit(currentNode); } }