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Add BFS.
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* [String Permutations](https://github.com/trekhleb/javascript-algorithms/tree/master/src/algorithms/string/permutations)
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* [String Permutations](https://github.com/trekhleb/javascript-algorithms/tree/master/src/algorithms/string/permutations)
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* Graph
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* Graph
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* [Depth-First Search (DFS)](https://github.com/trekhleb/javascript-algorithms/tree/master/src/algorithms/graph/depth-first-search)
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* [Depth-First Search (DFS)](https://github.com/trekhleb/javascript-algorithms/tree/master/src/algorithms/graph/depth-first-search)
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* [Breadth-First Search (BFS)](https://github.com/trekhleb/javascript-algorithms/tree/master/src/algorithms/graph/breadth-first-search)
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## Useful Links
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## Useful Links
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7
src/algorithms/graph/breadth-first-search/README.md
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7
src/algorithms/graph/breadth-first-search/README.md
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# Breadth-First Search (BFS)
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Breadth-first search (BFS) is an algorithm for traversing
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or searching tree or graph data structures. It starts at
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the tree root (or some arbitrary node of a graph, sometimes
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referred to as a 'search key') and explores the neighbor
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nodes first, before moving to the next level neighbors.
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import Graph from '../../../../data-structures/graph/Graph';
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import GraphVertex from '../../../../data-structures/graph/GraphVertex';
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import GraphEdge from '../../../../data-structures/graph/GraphEdge';
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import breadthFirstSearch from '../breadthFirstSearch';
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describe('breadthFirstSearch', () => {
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it('should perform BFS operation on graph', () => {
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const graph = new Graph(true);
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const vertexA = new GraphVertex('A');
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const vertexB = new GraphVertex('B');
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const vertexC = new GraphVertex('C');
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const vertexD = new GraphVertex('D');
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const vertexE = new GraphVertex('E');
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const vertexF = new GraphVertex('F');
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const vertexG = new GraphVertex('G');
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const vertexH = new GraphVertex('H');
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const edgeAB = new GraphEdge(vertexA, vertexB);
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const edgeBC = new GraphEdge(vertexB, vertexC);
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const edgeCG = new GraphEdge(vertexC, vertexG);
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const edgeAD = new GraphEdge(vertexA, vertexD);
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const edgeAE = new GraphEdge(vertexA, vertexE);
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const edgeEF = new GraphEdge(vertexE, vertexF);
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const edgeFD = new GraphEdge(vertexF, vertexD);
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const edgeDH = new GraphEdge(vertexD, vertexH);
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const edgeGH = new GraphEdge(vertexG, vertexH);
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graph
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.addEdge(edgeAB)
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.addEdge(edgeBC)
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.addEdge(edgeCG)
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.addEdge(edgeAD)
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.addEdge(edgeAE)
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.addEdge(edgeEF)
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.addEdge(edgeFD)
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.addEdge(edgeDH)
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.addEdge(edgeGH);
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expect(graph.toString()).toBe('A,B,C,G,D,E,F,H');
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const enterVertexCallback = jest.fn();
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const leaveVertexCallback = jest.fn();
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// Traverse graphs without callbacks first.
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breadthFirstSearch(graph, vertexA);
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// Traverse graph with enterVertex and leaveVertex callbacks.
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breadthFirstSearch(graph, vertexA, {
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enterVertex: enterVertexCallback,
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leaveVertex: leaveVertexCallback,
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});
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expect(enterVertexCallback).toHaveBeenCalledTimes(8);
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expect(leaveVertexCallback).toHaveBeenCalledTimes(8);
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expect(enterVertexCallback.mock.calls.toString()).toBe('A,B,D,E,C,H,F,G');
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expect(leaveVertexCallback.mock.calls.toString()).toBe('A,B,D,E,C,H,F,G');
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});
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it('should allow to create custom vertex visiting logic', () => {
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const graph = new Graph(true);
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const vertexA = new GraphVertex('A');
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const vertexB = new GraphVertex('B');
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const vertexC = new GraphVertex('C');
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const vertexD = new GraphVertex('D');
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const vertexE = new GraphVertex('E');
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const vertexF = new GraphVertex('F');
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const vertexG = new GraphVertex('G');
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const vertexH = new GraphVertex('H');
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const edgeAB = new GraphEdge(vertexA, vertexB);
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const edgeBC = new GraphEdge(vertexB, vertexC);
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const edgeCG = new GraphEdge(vertexC, vertexG);
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const edgeAD = new GraphEdge(vertexA, vertexD);
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const edgeAE = new GraphEdge(vertexA, vertexE);
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const edgeEF = new GraphEdge(vertexE, vertexF);
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const edgeFD = new GraphEdge(vertexF, vertexD);
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const edgeDH = new GraphEdge(vertexD, vertexH);
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const edgeGH = new GraphEdge(vertexG, vertexH);
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graph
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.addEdge(edgeAB)
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.addEdge(edgeBC)
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.addEdge(edgeCG)
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.addEdge(edgeAD)
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.addEdge(edgeAE)
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.addEdge(edgeEF)
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.addEdge(edgeFD)
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.addEdge(edgeDH)
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.addEdge(edgeGH);
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expect(graph.toString()).toBe('A,B,C,G,D,E,F,H');
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const enterVertexCallback = jest.fn();
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const leaveVertexCallback = jest.fn();
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// Traverse graph with enterVertex and leaveVertex callbacks.
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breadthFirstSearch(graph, vertexA, {
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enterVertex: enterVertexCallback,
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leaveVertex: leaveVertexCallback,
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allowTraversal: (vertex, neighbor) => {
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return !(vertex === vertexA && neighbor === vertexB);
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},
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});
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expect(enterVertexCallback).toHaveBeenCalledTimes(7);
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expect(leaveVertexCallback).toHaveBeenCalledTimes(7);
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expect(enterVertexCallback.mock.calls.toString()).toBe('A,D,E,H,F,D,H');
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expect(leaveVertexCallback.mock.calls.toString()).toBe('A,D,E,H,F,D,H');
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});
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});
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import Queue from '../../../data-structures/queue/Queue';
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/**
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* @typedef {Object} Callbacks
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* @property {function(vertex: GraphVertex, neighbor: GraphVertex): boolean} allowTraversal -
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* Determines whether DFS should traverse from the vertex to its neighbor
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* (along the edge). By default prohibits visiting the same vertex again.
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* @property {function(vertex: GraphVertex)} enterVertex - Called when DFS enters the vertex.
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* @property {function(vertex: GraphVertex)} leaveVertex - Called when DFS leaves the vertex.
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*/
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/**
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* @param {Callbacks} [callbacks]
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* @returns {Callbacks}
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*/
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function initCallbacks(callbacks = {}) {
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const initiatedCallback = callbacks;
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const stubCallback = () => {};
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const allowTraversalCallback = (
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() => {
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const seen = {};
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return (vertex, neighbor) => {
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if (!seen[neighbor.getKey()]) {
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seen[neighbor.getKey()] = true;
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return true;
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}
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return false;
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};
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}
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)();
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initiatedCallback.allowTraversal = callbacks.allowTraversal || allowTraversalCallback;
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initiatedCallback.enterVertex = callbacks.enterVertex || stubCallback;
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initiatedCallback.leaveVertex = callbacks.leaveVertex || stubCallback;
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return initiatedCallback;
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}
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/**
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* @param {Graph} graph
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* @param {GraphVertex} startVertex
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* @param {Callbacks} [rawCallbacks]
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*/
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export default function breadthFirstSearch(graph, startVertex, rawCallbacks) {
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const callbacks = initCallbacks(rawCallbacks);
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const vertexQueue = new Queue();
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// Do initial queue setup.
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vertexQueue.enqueue(startVertex);
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// Traverse all vertices from the queue.
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while (!vertexQueue.isEmpty()) {
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const currentVertex = vertexQueue.dequeue();
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callbacks.enterVertex(currentVertex);
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// Add all neighbors to the queue for future traversals.
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graph.getNeighbors(currentVertex).forEach((neighbor) => {
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if (callbacks.allowTraversal(currentVertex, neighbor)) {
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vertexQueue.enqueue(neighbor);
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}
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});
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callbacks.leaveVertex(currentVertex);
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}
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}
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@ -5,12 +5,3 @@ searching tree or graph data structures. One starts at
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the root (selecting some arbitrary node as the root in
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the case of a graph) and explores as far as possible
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the case of a graph) and explores as far as possible
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along each branch before backtracking.
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along each branch before backtracking.
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## Complexity
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* Time: O(|V| + |E|)
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* Space: O(|V|)
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## References
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[Wikipedia](https://en.wikipedia.org/wiki/Depth-first_search)
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