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67e26cfbae
* feat: Add ncr mod p code (#1323) * Update math/ncr_modulo_p.cpp Co-authored-by: David Leal <halfpacho@gmail.com> * Added all functions inside a class + added more asserts * updating DIRECTORY.md * clang-format and clang-tidy fixes forf6df24a5
* Replace int64_t to uint64_t + add namespace + detailed documentation * clang-format and clang-tidy fixes fore09a0579
* Add extra namespace + add const& in function arguments * clang-format and clang-tidy fixes for8111f881
* Update ncr_modulo_p.cpp * clang-format and clang-tidy fixes for2ad2f721
* Update math/ncr_modulo_p.cpp Co-authored-by: David Leal <halfpacho@gmail.com> * Update math/ncr_modulo_p.cpp Co-authored-by: David Leal <halfpacho@gmail.com> * Update math/ncr_modulo_p.cpp Co-authored-by: David Leal <halfpacho@gmail.com> * clang-format and clang-tidy fixes for5b69ba5c
* updating DIRECTORY.md * clang-format and clang-tidy fixes fora8401d4b
Co-authored-by: David Leal <halfpacho@gmail.com> Co-authored-by: github-actions <${GITHUB_ACTOR}@users.noreply.github.com>
205 lines
6.5 KiB
C++
205 lines
6.5 KiB
C++
/**
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*
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* \file
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* \brief [Breadth First Search Algorithm
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* (Breadth First Search)](https://en.wikipedia.org/wiki/Breadth-first_search)
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*
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* \author [Ayaan Khan](https://github.com/ayaankhan98)
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* \author [Aman Kumar Pandey](https://github.com/gpamangkp)
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*
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*
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* \details
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* Breadth First Search also quoted as BFS is a Graph Traversal Algorithm.
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* Time Complexity O(|V| + |E|) where V are the number of vertices and E
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* are the number of edges in the graph.
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*
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* Applications of Breadth First Search are
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*
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* 1. Finding shortest path between two vertices say u and v, with path
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* length measured by number of edges (an advantage over depth first
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* search algorithm)
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* 2. Ford-Fulkerson Method for computing the maximum flow in a flow network.
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* 3. Testing bipartiteness of a graph.
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* 4. Cheney's Algorithm, Copying garbage collection.
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*
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* And there are many more...
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*
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* <h4>working</h4>
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* In the implementation below we first created a graph using the adjacency
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* list representation of graph.
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* Breadth First Search Works as follows
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* it requires a vertex as a start vertex, Start vertex is that vertex
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* from where you want to start traversing the graph.
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* We maintain a bool array or a vector to keep track of the vertices
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* which we have visited so that we do not traverse the visited vertices
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* again and again and eventually fall into an infinite loop. Along with this
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* boolen array we use a Queue.
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*
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* 1. First we mark the start vertex as visited.
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* 2. Push this visited vertex in the Queue.
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* 3. while the queue is not empty we repeat the following steps
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*
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* 1. Take out an element from the front of queue
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* 2. Explore the adjacency list of this vertex
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* if element in the adjacency list is not visited then we
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* push that element into the queue and mark this as visited
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*
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*/
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#include <algorithm>
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#include <cassert>
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#include <iostream>
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#include <list>
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#include <map>
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#include <queue>
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#include <string>
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#include <vector>
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/**
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* \namespace graph
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* \brief Graph algorithms
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*/
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namespace graph {
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/* Class Graph definition */
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template <typename T>
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class Graph {
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/**
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* adjacency_list maps every vertex to the list of its neighbours in the
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* order in which they are added.
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*/
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std::map<T, std::list<T> > adjacency_list;
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public:
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Graph() = default;
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;
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void add_edge(T u, T v, bool bidir = true) {
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/**
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* add_edge(u,v,bidir) is used to add an edge between node u and
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* node v by default , bidir is made true , i.e graph is
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* bidirectional . It means if edge(u,v) is added then u-->v and
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* v-->u both edges exist.
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*
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* to make the graph unidirectional pass the third parameter of
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* add_edge as false which will
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*/
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adjacency_list[u].push_back(v); // u-->v edge added
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if (bidir == true) {
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// if graph is bidirectional
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adjacency_list[v].push_back(u); // v-->u edge added
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}
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}
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/**
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* this function performs the breadth first search on graph and return a
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* mapping which maps the nodes to a boolean value representing whether the
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* node was traversed or not.
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*/
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std::map<T, bool> breadth_first_search(T src) {
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/// mapping to keep track of all visited nodes
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std::map<T, bool> visited;
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/// initialise every possible vertex to map to false
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/// initially none of the vertices are unvisited
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for (auto const &adjlist : adjacency_list) {
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visited[adjlist.first] = false;
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for (auto const &node : adjacency_list[adjlist.first]) {
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visited[node] = false;
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}
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}
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/// queue to store the nodes which are yet to be traversed
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std::queue<T> tracker;
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/// push the source vertex to queue to begin traversing
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tracker.push(src);
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/// mark the source vertex as visited
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visited[src] = true;
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while (!tracker.empty()) {
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/// traverse the graph till no connected vertex are left
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/// extract a node from queue for further traversal
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T node = tracker.front();
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/// remove the node from the queue
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tracker.pop();
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for (T const &neighbour : adjacency_list[node]) {
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/// check every vertex connected to the node which are still
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/// unvisited
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if (!visited[neighbour]) {
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/// if the neighbour is unvisited , push it into the queue
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tracker.push(neighbour);
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/// mark the neighbour as visited
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visited[neighbour] = true;
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}
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}
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}
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return visited;
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}
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};
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/* Class definition ends */
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} // namespace graph
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/** Test function */
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static void tests() {
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/// Test 1 Begin
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graph::Graph<int> g;
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std::map<int, bool> correct_result;
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g.add_edge(0, 1);
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g.add_edge(1, 2);
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g.add_edge(2, 3);
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correct_result[0] = true;
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correct_result[1] = true;
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correct_result[2] = true;
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correct_result[3] = true;
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std::map<int, bool> returned_result = g.breadth_first_search(2);
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assert(returned_result == correct_result);
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std::cout << "Test 1 Passed..." << std::endl;
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/// Test 2 Begin
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returned_result = g.breadth_first_search(0);
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assert(returned_result == correct_result);
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std::cout << "Test 2 Passed..." << std::endl;
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/// Test 3 Begins
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graph::Graph<std::string> g2;
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g2.add_edge("Gorakhpur", "Lucknow", false);
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g2.add_edge("Gorakhpur", "Kanpur", false);
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g2.add_edge("Lucknow", "Agra", false);
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g2.add_edge("Kanpur", "Agra", false);
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g2.add_edge("Lucknow", "Prayagraj", false);
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g2.add_edge("Agra", "Noida", false);
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std::map<std::string, bool> correct_res;
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std::map<std::string, bool> returned_res =
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g2.breadth_first_search("Kanpur");
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correct_res["Gorakhpur"] = false;
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correct_res["Lucknow"] = false;
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correct_res["Kanpur"] = true;
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correct_res["Agra"] = true;
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correct_res["Prayagraj"] = false;
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correct_res["Noida"] = true;
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assert(correct_res == returned_res);
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std::cout << "Test 3 Passed..." << std::endl;
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}
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/** Main function */
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int main() {
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tests();
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size_t edges = 0;
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std::cout << "Enter the number of edges: ";
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std::cin >> edges;
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graph::Graph<int> g;
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std::cout << "Enter space-separated pairs of vertices that form edges: "
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<< std::endl;
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while (edges--) {
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int u = 0, v = 0;
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std::cin >> u >> v;
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g.add_edge(u, v);
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}
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g.breadth_first_search(0);
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return 0;
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}
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