Breadth First Traversal

Depth and breadth first tree traversal - Dhruba Bandopadhyay

A friend of mine mentioned depth and breadth first tree traversal today and since I didn’t have a post on this already I thought this would be a good opportunity to do one and post my take on it. This focuses more on depth and breadth first tree traversal as opposed to graph search and whereas the algorithm is identical to how you’d expect an iterative dfs/bfs traversal to be there are a couple of small differences in the way I’ve done it here which may be serve as useful tips.

Node

The first thing we need is the classic Node class which has an identity and children.

package name.dhruba.kb.algos.dfsbfs; class Node { final String name; final Node[] children; Node(String name) { this.name = name; this.children = new Node[0]; } Node(String name, Node[] children) { this.name = name; this.children = children; } boolean hasChildren() { return children != null && children.length > 0; } @Override public String toString() { return name; } } Depth and breadth first traversal

Now here is the depth and breadth first traversal algorithm. Observations on the code follow underneath.

package name.dhruba.kb.algos.dfsbfs; import java.util.ArrayDeque; import java.util.Deque; import org.slf4j.Logger; import org.slf4j.LoggerFactory; class DfsBfsTraverser { static final Logger logger = LoggerFactory.getLogger(DfsBfsTraverser.class); enum TraversalType { DEPTH_FIRST, BREADTH_FIRST; } interface NodeProcessor { void process(Node node); } static void traverse(Node root, TraversalType traversalType, NodeProcessor processor) { if (root == null) { return; } if (!root.hasChildren()) { processor.process(root); return; } Deque<Node> deck = new ArrayDeque<Node>(); addToDeck(deck, traversalType, root); while (!deck.

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