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What is f reachable queue?
A reachable queue is a data structure used in computer science, particularly in graph theory and algorithms. It represents a queue of elements that can be accessed or processed based on certain criteria, often related to their reachability from a starting point in a graph. Elements in the reachable queue are typically those that can be reached from a specified node, allowing efficient traversal and manipulation of graph data. This concept is often utilized in algorithms like breadth-first search (BFS) for exploring nodes in a graph.
How do you write a c program for performing DFS and BFS operations?
#include<stdio.h> #include<conio.h> #include<alloc.h> #include<process.h> #include<string.h> #define MAX 20 typedef struct queue { int data; struct queue *next; }queue; typedef struct stack { int data; struct stack *next; }stack; typedef struct adj_list { int vertex; struct adj_list *next; }adj_list; adj_list *G[MAX]; int queue_empty(queue *front,queue *rear) { if(front==NULL && rear==NULL) return 1; else return 0; } queue* getnode() { queue *newnode; newnode = (queue*)malloc(sizeof(queue)); newnode->next = NULL; return newnode; } void enqueue(queue **front, queue **rear, int data) { queue *newnode; newnode = getnode(); newnode->data = data; if(queue_empty(*front,*rear)) { *front = *rear = newnode; } else { (*rear)->next = newnode; (*rear) = newnode; } } int dequeue(queue **front,queue **rear) { int data; queue *temp; if(queue_empty(*front,*rear)) return 0; temp = *front; data = (*front)->data; if(*front==*rear) { *front = *rear = NULL; } else { *front = (*front)->next; } free(temp); return data; } stack* create_node() { stack *newnode; newnode = (stack*)malloc(sizeof(stack)); newnode->next = NULL; return newnode; } void push(stack **top, int data) { stack *newnode; newnode = create_node(); newnode->data = data; newnode->next = *top; *top = newnode; } int pop(stack **top) { stack *temp; int data; temp = *top; data = (*top)->data; *top = (*top)->next; free(temp); return data; } int stack_empty(stack *top) { if(top==NULL) return 1; else return 0; } void insert(int vi, int vj) { adj_list *temp,*newnode; newnode=(adj_list*)malloc(sizeof(adj_list)); newnode->vertex = vj; newnode->next=NULL; if(G[vi]==NULL) { G[vi]=newnode; } else { temp = G[vi]; while(temp->next!=NULL) { temp = temp->next; } temp->next = newnode; } } void create(int count,char location[MAX][MAX]) { int i,edges, vi,vj; for(i=0;i<count;i++) { printf("\nEnter the name of node %d\t",i); flushall(); scanf("%s",location[i]); G[i] = NULL; } printf("\nEnter number of edges\t"); scanf("%d",&edges); for(i=0;i<edges;i++) { printf("\nEnter the edge (node u,node v)\t"); scanf("d",&vi,&vj); insert(vi,vj); insert(vi,vj); } } void BFS(int v,int count,char location[MAX][MAX]) { int w,i,visited[MAX]; queue *front=NULL,*rear=NULL; adj_list *temp; for(i=0;i<count;i++) { visited[i]=0; } enqueue(&front,&rear,v); printf("\n%s",location[v]); visited[v]=1; while(!queue_empty(front,rear)) { v = dequeue(&front,&rear); for(temp=G[v];temp!=NULL;temp=temp->next) { w = temp->vertex; if(visited[w]==0) { enqueue(&front,&rear,w); visited[w]=1; printf("\n%s",location[w]); } } } } void DFS(int v,int count,char location[MAX][MAX]) { adj_list *temp; int visited[MAX],j,w; stack *top=NULL; for(j=0;j<count;j++) { visited[j]=0; } push(&top,v); visited[v]=1; while(!stack_empty(top)) { w = pop(&top); printf("\n%s",location[w]); for(temp=G[w];temp!=NULL;temp=temp->next) { if(visited[temp->vertex]==0) { push(&top,temp->vertex); visited[temp->vertex]=1; } } } } int search(char location[MAX][MAX], char item[MAX]) { int i; for(i=0;i<MAX;i++) { if(stricmp(item,location[i])==0) /*string found*/ return i; } return -1; } void main() { int ch,count,i; char location[MAX][MAX],start[MAX]; do { clrscr(); printf("\n*** MENU ***"); printf("\n1.Create"); printf("\n2.Depth First Search"); printf("\n3.Breadth First Search"); printf("\n4.Exit"); printf("\n\nEnter your choice\t"); scanf("%d",&ch); switch(ch) { case 1: printf("\nEnter number of nodes\t"); scanf("%d",&count); create(count,location); break; case 2: printf("\nEnter starting place\t"); scanf("%s",start); i = search(location,start); if(i==-1) printf("\nInvalid Location Entered"); else { printf("\nDepth First Search...\n"); DFS(i,count,location); } break; case 3: printf("\nEnter starting place\t"); scanf("%s",start); i = search(location,start); if(i==-1) printf("\nInvalid Location Entered"); else { printf("\nBreadth First Search...\n"); BFS(i,count,location); } break; case 4:exit(0); default:printf("\nPlease enter proper choice!!!"); } getch(); }while(1); } This program performs both DFS and BFS operations.
Prove that if a DFS and BFS trees in graph G are the same than?
ok here we go...Proof:If the some graph G has the same DFS and BFS then that means that G should not have any cycle(work out for any G with a cycle u will never get the same BFS and DFS .... and for a graph without any cycle u will get the same BFS/DFS).We will prove it by contradiction:So say if T is the tree obtained by BFS/DFS, and let us assume that G has atleast one edge more than T. So one more edge to T(T is a tree) would result in a cycle in G, but according to the above established principle no graph which has a cycle would result the same DFS and BFS, so out assumption is a contradiction.Hence G should have more edges than T, which implies that if the BFS and DFS for a graph G are the same then the G = T.Hope this helps u......................
Explain why there are no forward non tree edges with respect to a BFS tree constructed for a directed graph?
bag
How do you implement depth first search in C using arrays?
#include<stdio.h> #include<conio.h> char que[20]; int front=0, rear=0, n; char arr[20]; int bfs(int ); char ajMat[20][20]; char b[20]; void display(); int p=0; int main() { char v; printf("Enter the number of nodes in a graph"); scanf("%d",&n); printf("Enter the value of node of graph"); for(int i=0; i<n; i++) { scanf("%s",&b[i]); } printf("Enter the value in adjancency matrix in from of 'y' or 'n'\n"); printf("If there exits an edge between two vertices than 'y' otherwise 'n'\n"); for(int i=0; i<n; i++) printf(" %c ",b[i]); for(int i=0;i<n; i++) { printf("\n%c ",b[i]); for(int j=0; j<n; j++) { printf("%c ",v=getch()); ajMat[i][j]=v; } printf("\n\n"); } for(int i=0;i<n;i++) bfs(i); display(); getch(); } void display() { printf("BFS of Graph : "); for(int i=0; i<n; i++) printf("%c ",arr[i]); } void insert(char val) { que[front]=val; front++; } char del() { rear=rear+1; return que[rear-1]; } bool unVisit(char val) { for(int i=0; i<front; i++) { if(val==que[i]) return false; } return true; } int bfs(int i) { char m; if(front==0) { insert(b[i]); } for(int j=0; j<n; j++) { if(ajMat[i][j]=='y') { if(unVisit(b[j])) { insert(b[j]); } } } m=del(); arr[p]=m; p++; return 0; }
Is BFS recursive?
No, Breadth-First Search (BFS) is not inherently recursive. It is typically implemented using a queue data structure rather than recursion.
Is it possible for Breadth-First Search (BFS) to be implemented recursively"?
Yes, Breadth-First Search (BFS) can be implemented recursively, but it is not the most efficient method compared to using a queue-based iterative approach.
How can the Breadth-First Search (BFS) algorithm be implemented using recursion?
The Breadth-First Search (BFS) algorithm can be implemented using recursion by using a queue data structure to keep track of the nodes to visit. The algorithm starts by adding the initial node to the queue and then recursively visits each neighbor of the current node, adding them to the queue. This process continues until all nodes have been visited.
Difference between DFS and BFS?
1. bfs uses queue implementation ie.FIFO dfs uses stack implementation ie. LIFO 2. dfs is faster than bfs 3. dfs requires less memory than bfs 4. dfs are used to perform recursive procedures.
Can you implement Breadth-First Search (BFS) recursively?
Yes, Breadth-First Search (BFS) can be implemented recursively by using a queue data structure to keep track of the nodes to visit next. The algorithm involves visiting each node at the current level before moving on to the next level.
How do you search for nodes in a binary tree by level in PHP?
To search for nodes in a binary tree by level in PHP, you can use a breadth-first search (BFS) approach, typically implemented with a queue. Start by initializing a queue with the root node, then iteratively dequeue nodes, processing them level by level. For each node, enqueue its children until all nodes are visited. This method allows you to access nodes level by level efficiently.
Can you explain how the Breadth-First Search (BFS) algorithm works in graph traversal?
The Breadth-First Search (BFS) algorithm starts at a chosen node and explores all its neighbors before moving on to the next level of neighbors. It uses a queue data structure to keep track of the nodes to visit next. This process continues until all nodes have been visited. BFS is effective for finding the shortest path in unweighted graphs.
Who is faster between dfs and bfs?
dfs better then from bfs..
What is f reachable queue?
A reachable queue is a data structure used in computer science, particularly in graph theory and algorithms. It represents a queue of elements that can be accessed or processed based on certain criteria, often related to their reachability from a starting point in a graph. Elements in the reachable queue are typically those that can be reached from a specified node, allowing efficient traversal and manipulation of graph data. This concept is often utilized in algorithms like breadth-first search (BFS) for exploring nodes in a graph.
What is the population of BFS Group Ltd?
The population of BFS Group Ltd is 4,200.
What are the key differences between Breadth-First Search (BFS) and Dijkstra's algorithm, and how do these differences impact their respective efficiencies in finding the shortest path in a graph?
Breadth-First Search (BFS) explores all neighbors of a node before moving on to the next level, while Dijkstra's algorithm prioritizes nodes based on their distance from the start node. This means BFS may not always find the shortest path, especially in weighted graphs, whereas Dijkstra's algorithm guarantees the shortest path. Dijkstra's algorithm is more efficient in finding the shortest path in weighted graphs due to its priority queue implementation, while BFS is more efficient in unweighted graphs.
Can anyone be jb bfs?
No. why
