print shortest path gfg practice.  Here adj [i] contains vectors of size 2,Frequencies of Limited Range Array Elements. print shortest path gfg practice

 
 Here adj [i] contains vectors of size 2,Frequencies of Limited Range Array Elementsprint shortest path gfg practice  The graph is represented as an adjacency

Shortest path in a graph from a source S to destination D with exactly K edges for multiple Queries. Follow the steps. Note: You can only move either down or right at any point in time. At any step i, we can move forward i, then backward i + 1. package ga; import java. Set value of count [i] [0] equal to 1 for 0 <= i < M as the answer of subproblem with a single column is equal to 1. Step 4: Find the minimum among these edges. Approach: An O (V^3*K) approach for this problem has already been discussed in the previous article. Find the minimum number of steps required to reach from (0,0) to (X, Y). It has to reach the destination at (N - 1, N - 1). Expected Time Complexity: O (n*m) Expected Space Compelxity: O (n) Constraints: 1 <= n <= 100. It contains well written, well thought and well explained computer science and programming articles, quizzes and practice/competitive programming/company interview Questions. Print all nodes that are at distance k from root (root is considered at distance 0 from itself). For target node 8 and k is 2, the node 22 comes in this category. Shortest path in Undirected Graph having unit distance | Practice | GeeksforGeeks. 0 <= m <= n* (n-1), where m is the total number of Edges in the. Your task is to complete the function Paths () that takes the root node as an argument and return all the possible path. Initialize a counter [] [] vector, this array will keep track of the number of remaining obstacles that can be eliminated for each visited cell. Below is a recursive solution suggested by Arpit Thapar here . Introduction to Kruskal’s Algorithm: Here we will discuss Kruskal’s. def BFS_SP (graph, start,. Bellman–Ford algorithm is slower than Dijkstra’s Algorithm, but it can handle negative weights edges in the graph, unlike Dijkstra’s. Shortest path from source to destination such that edge weights along path are alternatively increasing and decreasing. Practice. The task is to find the shortest path from the start node to the end node and print the path in the form of directions given below. The algorithm maintains a set of visited vertices. &nbsp; Example 1: Input: n = 3, edges. If there is no possible path, return -1. Check if it is possible to make all elements into 1 except obstacles. Approach: The solution is to perform BFS or DFS to find whether there is a path or not. You are given an integer K and source src and destination dst. We can. Print all root to leaf paths of an N-ary tree. The path can only be created out of a cell if its value is 1. Practice. Keep&nbsp;the following conditions in mYour task is to complete the function printGraph () which takes the integer V denoting the number of vertices and edges as input parameters and returns the list of list denoting the adjacency list. We define ‘ g ’ and ‘ h ’ as simply as possible below. Sort all the edges in non-decreasing order of their weight. Given a Directed Acyclic Graph of N vertices from 0 to N-1 and a 2D Integer array (or vector) edges [ ] [ ] of length M, where there is a directed edge from edge [i] [0] to edge [i] [1] with. For example, the following graph has eulerian cycle as {1, 0, 3, 4, 0, 2, 1}Input: For given graph G. Feeling lost in the world of random DSA topics, wasting time without progress?. Here reachable mean that there is a path from vertex i to j. Length of shortest safe route is 13. Given a directed graph. Iterate over all M edges and for each edge U and V set dp [U] [V] to 1 and ANS [U] [V] to A [U] + A [V]. Expected Time Complexity: O (R * C) Expected Auxiliary Space: O (1) Constraints: 1 <= R,C <= 103. Problem here, is a generalized version of the. Like Articulation Points, bridges represent vulnerabilities in a connected network and are. Print all paths from a given source to a destination using BFS; Find if there is a path between two vertices in a directed graph; Islands in a graph using BFS; Water Jug problem using BFS; Level of Each node in a Tree from source node (using BFS) Word Ladder (Length of shortest chain to reach a target word)Given a Directed Graph with V vertices (Numbered from 0 to V-1) and E edges, check whether it contains any cycle or not. Johnson's algorithm for All-pairs shortest paths; Shortest Path in Directed Acyclic Graph; Multistage Graph (Shortest Path) Shortest path in an unweighted graph; Karp's minimum mean (or average) weight cycle algorithm; 0-1 BFS (Shortest Path in a Binary Weight Graph) Find minimum weight cycle in an undirected graph Explanation: There exists no path from start to end. Follow the steps mentioned below to implement the idea: Create a recursive function. Copy contents. Your task is to complete the function chinesePostmanProblem () which takes the edge list e [] [], number of nodes as input parameters and returns the length of the shortest path that visits each edge at least once. Let’s call it. Time Complexity: O (R * C), where R is number of rows and C are the number of columns in the given matrix. (weight, vertex). Output: 2. If zero or two vertices have odd degree and all other vertices have even degree. North, East, West and South where n is value of the cell , We can move to mat [i+n] [j], mat [i-n] [j], mat [i] [j+n], and mat [i] [j-n. Time Complexity: O(N 2) Efficient Approach: The idea is to use Recursion to solve this problem efficiently. } and dist [s] = 0 where s is the source. Below is the implementation of the above approach:Given a Binary Tree of size N, you need to find all the possible paths from root node to all the leaf node's of the binary tree. If source is already any of the corner then. Using this it's clear to see that you can generate the shortest path with one linear scan of a topological ordering (pseudocode): Graph g Source s top_sorted_list = top_sort (g) cost = {} // A mapping between a node, the cost of its shortest path, and //its parent in the shortest path for each vertex v in top_sorted_list: cost [vertex]. Practice. Approach: The shortest path can be searched using BFS on a Matrix. Given a 2-D binary matrix of size n*m, where 0 represents an empty space while 1 represents a wall you cannot walk through. e. Unique paths covering every non-obstacle block exactly once in a grid. Example1: Input: N = 4, M = 2 edge = [[0,1,2],[0,2,1]] Output: 0 2 1 -1 Explanation: Shortest path from 0 to 1 is 0->1 with edge weight 2. Also go through detailed tutorials. Follow the below steps to solve the above problem: 1) Start at the root node and push it onto a stack. Consider a directed graph whose vertices are numbered from 1 to n. Johnson’s algorithm finds the shortest paths between all pairs of vertices in a weighted directed graph. Paytm. Medium Accuracy: 32. 2) Create a separate stack to store the path from the root to the current node. If the popped node is the destination node, return its distance. Naive Approach: The idea is to generate all possible paths from the root node to all leaf nodes, keep track of the path with maximum length, finally print the longest path. Change the value of matrix [0] [2] and matrix [1] [2] to 0 and the path is 0,0 -> 0,1 -> 0,2 -> 1,2 -> 2,2. , grid [0] [0]). When we find “. U = 1, V = 3. Consider the following directed graph. (The values are returned as vector in cpp, as. Path is:: 2 1 0 3 4 6. Output − List of the shortest distance of all vertices from the starting node. Given a 2-D binary matrix of size n*m, where 0 represents an empty space while 1 represents a wall you cannot walk through. Shortest Path-Printing using Dijkstra's Algorithm for Graph (Here it is implemented for undirected Graph. Print all shortest paths between given source and destination in an undirected graph. e. You&nbsp;need to find the shortest distance&nbsp;between a given source cell to a destination cell. Courses. Note: All weights are non-negative. Print root to leaf paths without using recursion. The path can only be created out of a cell if its value is 1. Also go through detailed tutorials to improve your understanding to the topic. Then the LIP value for cell m [0] [0] will be the answer. This algorithm is used to find a loop in a linked list. We initialize distances to all vertices as minus infinite and. Therefore, BFS is an appropriate algorithm to solve this problem. in all 4 directions. Time Complexity: O (N), the time complexity of this algorithm is O (N), where N is the number of nodes in the tree. For Example, in the above binary tree the path between the nodes 7 and 4 is 7 -> 3 -> 1 -> 4 . The robot tries to move to the bottom-right corner (i. Find shortest possible path to type all characters of given string using the remote. You need to find the shortest distance between a given source cell to a destination cell. Step 2: Follow steps 3 to 5 till there are vertices that are not included in the MST (known as fringe vertex). 1) Nodes in the subtree rooted with target node. Approach: The main idea here is to use a matrix (2D array) that will keep track of the next node to point if the shortest path changes for any pair of nodes. , we use Topological Sorting . Single source shortest path between two cities. Given a&nbsp;2D binary matrix A(0-based index) of dimensions NxM. Meet In The Middle solution is similar to Dijkstra’s solution with some modifications. Given a Binary Tree of size N and an integer K. GfG Weekly + You = Perfect Sunday Evenings! Register for free now. Recommended: Please solve it on “ PRACTICE ” first, before moving on to the solution. Given two strings X and Y, print the shortest string that has both X and Y as subsequences. Following is the Backtracking algorithm for Knight’s tour problem. Dijkstra in 1956. Approach: The idea is to use topological sorting, Follow the steps mentioned below to solve the problem: Represent the sequences in the ‘ arr [] [] ’ by a directed graph and find its topological sort order. The rat can move only in two directions: forward and down. If the destination is reached, print the vector as one of the possible paths. 89% Submissions: 109K+ Points: 4. . Given two strings, find the length of longest subsequence present in both of them. For example, lcs of “geek” and “eke” is “ek”. . Therefore, BFS is an appropriate algorithm to solve this problem. Count cells in a grid from which maximum number of cells can be reached by K vertical or horizontal jumps. The idea is similar to linear time solution for shortest path in a directed acyclic graph. Share. Overview. The given two nodes are guaranteed to be in the binary tree and nodes are numbered from 1 to N. Complete the function booleanMatrix () that takes the matrix as input parameter and modifies it in-place. In the main function, create a binary tree using the newNode function, and call the leftMostShortest function with the root node. Try all 8 possible positions where a Knight can reach from its position. A person wants to go from origin to a particular location, he can move in only 4 directions (i. Explanation: The shortest path is: 2 → 1. Eventually, the shortest path, if one exists, is found and the spring has been relaxed to its resting length. Examples: Input: X = "AGGTAB", Y = "GXTXAYB" Output: "AGXGTXAYB" OR "AGGXTXAYB" OR Any string that represents shortest supersequence of X and Y Input:. 2K 161 You have an undirected, connected graph of n nodes labeled from 0 to n - 1. Explanation: (1, 2) and (2, 5) are the only edges resulting into shortest path between 1 and 5. Below is algorithm based on set data structure. A Simple Solution is to use Dijkstra’s shortest path algorithm, we can get a shortest path in O (E + VLogV) time. e. Practice. Explanation: The first and last node of the input sequence is 1 and 4 respectively. Dijkstra. Note: The Graph doesn't contain any negative weight cycle. Every item of set is a pair. Menu. Back to Explore Page. Given an n x n binary matrix grid, return the length of the shortest clear path in the matrix. A solution that always finds shortest superstring takes exponential time. The sum of weight in the above path is -3 + 2 – 1 = -2. Initialising the Next array. Path to reach border cells from a given cell in a 2D Grid without crossing specially marked cells. Given adjacency list adj as input parameters . However, the longest path problem has a linear time solution for directed acyclic graphs. Given a directed graph where every edge has weight as either 1 or 2, find the shortest path from a given source vertex ‘s’ to a given destination vertex ‘t’. You are given an Undirected Graph having unit weight, Find the shortest path from src to all the vertex and if it is unreachable to reach any vertex, then return -1 for that vertex. Time Complexity: O(N 2) Auxiliary Space: O(N) Efficient Approach:The problem can be solved. Input: root = [2, 1], startValue = 2, destValue = 1. org. You have to return a list of integers denoting shortest distance between each node and Source vertex S. Approach 1: By looking at examples we can see that the above simplification process just behaves like a stack. Consider a directed graph whose vertices are numbered from 1 to n. Simple Approach: A naive approach is to calculate the length of the longest path from every node using DFS . Method 1 (Simple) One straight forward solution is to do a BFS traversal for every node present in the set and then find all the reachable nodes. The Greedy Choice is to pick the edge that connects the two sets and is on the smallest weight path from the source to the set that contains not yet included vertices. Weight (or distance) is used. &nbsp; If the pat. Hence, the shortest distance. Example 2: Input: Output: 1 Explanation: The output 1 denotes that the order is valid. 2) Assign a distance value to all vertices in the input graph. Given a directed acyclic graph (DAG) of n nodes labeled from 0 to n - 1, find all possible paths from node 0 to node n - 1 and return them in any order. Distance from the Source (Bellman-Ford Algorithm) | Practice | GeeksforGeeks. Minimum time to visit all nodes of given Graph at least once. Output. Given a directed graph, find out if a vertex j is reachable from another vertex i for all vertex pairs (i, j) in the given graph. Shortest Source to Destination Path | Practice | GeeksforGeeks Back to Explore Page Given a 2D binary matrix A (0-based index) of dimensions NxM. Your Task: You don't need to read input or print anything. 1) Initialize distances of all vertices as infinite. Problem Statement: . Explanation: The number of shortest path from node 1 to node 4 is 2, having cost 5. Strings are defined as an array of characters. Remove nodes from Binary Tree such that sum of all remaining root-to-leaf paths is atleast K. If the length of the shortest path. Dijkstra's shortest path algorithm in Java using PriorityQueue. This problem is mainly an extension of Find distance between two given keys of a Binary Tree. Repeat step#2 until there are (V-1) edges in the. Given a weighted directed graph with N vertices and M edges, a source src and a destination target, the task is to find the shortest monotonic path (monotonically increasing or decreasing) from the source to the destination. Num1 and Num2 are prime numbers. Shortest path in a directed graph by Dijkstra’s algorithm. Dijkstra’s shortest path for adjacency matrix representation. Bellman-Ford is a single source shortest path algorithm that determines the shortest path between a given source vertex and every other vertex in a graph. Print a given matrix in spiral form using the simulation approach: To solve the problem follow the below idea: Draw the path that the spiral makes. Top-down approach for printing Longest Common Subsequence: Follow the steps below for the implementation: Check if one of the two strings is of size zero, then we return an empty string because the LCS, in this case, is empty (base case). Menu. a) Find the most overlapping string pair in temp []. The idea is to use Dijkstra’s algorithm to find the shortest path from source vertex a to all other vertices in the graph using the straight edges and store the result in array da[], and then from the destination vertex b to all other vertices and store the result in db[]. You are also given an integer k. If you like GeeksforGeeks and would like to. Now he calculated if there is any Eulerian Path in that graph. If there is an Eulerian path then there is a solution otherwise not. Approach: This problem is similar to finding the shortest path in an unweighted graph. Note:&nbsp;edges [i] is&nbsp;defined as u, v and weight. It's a common practice to augment dynamic programming algorithms to store parent pointers. e. Input : str = "ABC". If a vertices can't be reach from the S then mark the distance as 10^8. e. If it is unreachable then return -1. In this article, an even optimized recursive approach will be discussed. One possible Topological order for the graph is 5, 4, 2, 1, 3, 0. You don't need to read input or print anything. util. Your Task:Your task is to complete the function isNegativeWeightCycle () which takes n and edges as input paramater and returns 1 if graph contains negative weight cycle otherwise returns 0. Approach: Use recursion to move first right then down from each cell in the path of the matrix mat[][], starting from source, and store each value in a vector. Following is complete algorithm for finding shortest distances. Therefore, BFS is an appropriate algorithm to solve this problem. Back to Explore Page. If current character, i. Let arr [] be given set of strings. Your Task: You don't have to take input. Given a boolean matrix of size RxC where each cell contains either 0 or 1, modify it such that if a matrix cell matrix [i] [j] is 1 then all the cells in its ith row and jth column will become 1. Your Task: You don't need to read or print anything. Given edges, s and d ,count the number of. Find Longest Common Subsequence (lcs) of two given strings. Time Complexity: O (V+E) where V is the number of vertices and E is the number of edges. i. The time complexity for the matrix representation is O (V^2). Step 2: Define a function “findLongestFromACell” that takes in a cell’s row and column index, the matrix, and a lookup table. So the path which will cover all the points is (1, 4) and (4, 1) on the coordinate axis. Example1: Input: N = 4, M = 2 edge =. The path can only be constructed out of cells having value 1, and at any moment, we can only move one step in one of the four directions. Given a weighted directed graph with n nodes and m edges. Back to Explore Page. We have discussed Dijkstra’s algorithm and its implementation for adjacency matrix representation of graphs. The task is to count&nbsp;all distinct nodes that are distance k from a leaf node. So the space needed is O(V). Note : You can move into an adjacent cell if that adjacent cell is filled with element 1. It may cause starvation if shorter processes keep coming. Trade-offs between BFS and DFS: Breadth-First search can be useful to find the shortest path between nodes, and. Johnson's algorithm for All-pairs shortest paths; Shortest Path in Directed Acyclic Graph; Multistage Graph (Shortest Path) Shortest path in an unweighted graph; Karp's minimum mean (or average) weight cycle algorithm; 0-1 BFS (Shortest Path in a Binary Weight Graph) Find minimum weight cycle in an undirected graphExplanation: There exists no path from start to end. Approach: The idea is to traverse all vertices of the graph using BFS and use priority queue to store the vertices for which the shortest distance. Contests. Solve company interview questions and improve your coding intellectUnique Paths II - You are given an m x n integer array grid. Medium Accuracy: 32. Practice. ” in our path, we simply pop the topmost element as we have to jump back to parent’s directory. Given a weighted, directed and connected graph of V vertices and E edges, Find the shortest distance of all the vertex's from the source vertex S. Initially, the shortest path between any two nodes u and v is v (that is the direct edge from u -> v). Print all paths from a given source to a destination using BFS. Relax all the edges (u,v,weight) N-1 times as per the below condition: dist [v] = minimum (dist [v], distance. Modify the above solution to find weight of longest path from a given source. To solve the problem follow the below idea: This problem can be seen as the shortest path in an unweighted graph. The following steps can be followed to compute the result: If the source is equal to the destination then return 0. Whenever we encounter any file’s name, we simply push it into the stack. You don't need to read input or print anything. GfG-Problem Link: and Notes Link: a weighted, undirected and connected graph of V vertices and E edges. (a) Calculate the shortest path from s to all other vertices by using the Dijkstra algorithm. . The task is to find the&nbsp;lowest common ancestor of the given two nodes. e. Auxiliary Space: O (R*C), The extra space is used in storing the elements of the visited matrix. Minimum steps to reach the target by a Knight using BFS:. The reach-ability matrix is called the transitive closure of a graph. Example 1: Input: 1 2 3 4 5 6. &nbsp; Example 1: Input: n = 3, edges. You can also go from S=1 to T=8 via (1, 2, 5, 8) or (1, 4, 6, 7, 8) but these paths are not shortest. Auxiliary Space: O (V) 5. Given a Binary Tree and a positive integer k. Step 2: Pick edge 8-2. Your Task: You don't need to read input or print anything. It follows Greedy Approach. The task is to print the cyclic path whose sum of weight is negative. , grid [m - 1] [n - 1]). Expected Time Compelxity: O (n2*log (n)) Expected Auxiliary Space: O (n2) Constraints: 1 ≤ n ≤ 500. Monotonic shortest path from source to destination in Directed Weighted Graph. 1. So, if you have, implemented your function correctly, then output would be 1 for all test cases. Method 1. Output: Yes. If multiple shortest supersequence exists, print any one of them. Initialize a queue data structure that contains a list that will be composed of the. Expected Time Compelxity: O (n2*log (n)) Expected Auxiliary Space: O (n2) Constraints: 1 ≤ n ≤ 500. Check if not the base case, then if we have a solution for the current a and b saved in the memory, we. Input: i = 4, j = 3. Courses. The graph contains 9 vertices and 14 edges. Given a Binary Tree of size N, you need to find all the possible paths from root node to all the leaf node's of the binary tree. Graph is in the form of adjacency list where adj [i] contains all the nodes ith node is having edge with. Pop the top-most element from pq. Return d (s) as the shortest path from s to t. Discuss. You don't need to read input or print anything. Using the fact that the second shortest path can not contain all the edges same as that in the shortest path. 4) Huffman. There is an edge from a vertex i to a vertex j iff either j = i + 1 or j = 3 * i. The Minimum distance of all nodes from Source, intermediate, and destination can be found by doing Dijkstra’s Shortest Path algorithm from these 3. Step 4: if the subsequence is not in the list then recur. Naive Approach: The idea is to use Floyd Warshall Algorithm. If there is only one topological sort. We maintain two sets: a set of the vertices already included in the tree and a set of the vertices not yet included. Nodes are labeled from 0 to n-1, the task is to check if it contains a negative weight cycle or not. Print path between any two nodes in a Binary Tree; Preorder Traversal of Binary Tree; Count pairs of leaf nodes in a Binary Tree which are at most K distance apart; Print all root-to-leaf paths with maximum count of even nodes; Count nodes having highest value in the path from root to itself in a Binary Tree; Height and Depth of a node in a. If the path exists between two nodes then Next [u] [v] = v. Practice. If k is more that height of tree, nothing should be prin. Given an undirected graph with V vertices and E edges, check whether it contains any cycle or not. Example 1: Input: A = 6, B = 6. Weight (or. He considered each of the lands as a node of a graph and each bridge in between as an edge in between. Step-2: Pick all the vertices with in-degree as 0 and add them into a queue (Enqueue operation) Step-3: Remove a vertex from the. Find the length of the shortest transformation sequence from startWord to targetWord. Traverse all words that adjacent (differ by one character) to it and push the word in a queue (for BFS)A rat starts from source and has to reach the destination. Output: Shortest path length is:2 Path is:: 0 3 7 Input: source vertex is = 2 and destination vertex is. 2 Given node s nd shortest path from s to all other nodes. Transitive closure of above graphs is 1 1 1 1 1 1. Hard Accuracy: 50. In other words, the shortest path from S to X is the minimum over all paths that go from S to U, then have an edge from U to X, where U is some vertex in S. Follow the steps below to solve the problem: Create dp [N] [N] and ANS [N] [N] tables with all values set to INT_MAX and INT_MIN. We can only traverse to adjacent element, i. The graph is given as follows: graph[i] is a list of all nodes you can visit from node i (i. 1 ≤ cost of cells ≤ 1000. Practice. Example: Input: n = 9, m= 10 edges= [ [0,1], [0,3], [3,4. Method 1: Recursive. Examples: Input: Root of below tree And x = pointer to node 13 10 / . Naive Approach: The simplest approach to solve this problem is to first construct the graph using the given conditions, then find the shortest path between the nodes using a and b using bfs by considering a as the source node of the graph. ” we do nothing. Bellman-Ford is a single source shortest path algorithm that determines the shortest path between a given source vertex and every other vertex in a graph. You are given a weighted undirected graph having n+1 vertices numbered from 0 to n and m edges describing there are edges between a to b with some weight, find the shortest path between the vertex 1 and the vertex n, and if the path does not exist then return a list consisting of only-1. Shortest path in grid with obstacles. Practice. 89% Submissions: 109K+ Points: 4. Shortest direction | Practice | GeeksforGeeks. In the path list, for each unvisited vertex, add the copy of the path of its. The Ford-Fulkerson algorithm is a widely used algorithm to solve the maximum flow problem in a flow network. Input: N = 5, M = 8. Below is the implementation of the approach. You are. 2) Create an empty priority_queue pq. Your task is to complete the function findShortestPath () which takes matrix as input parameter and return an integer denoting the shortest path. 64 %. Practice. Start with the source node s and set its shortest path estimate to 0. If there is no possible path, return -1. A Graph is a non-linear data structure consisting of vertices and edges. /. Given two four digit prime numbers, suppose 1033 and 8179, we need to find the shortest path from 1033 to 8179 by altering only single digit at a time such that every number that we get after changing a digit is prime. Example 1: Input: 1 / 2 3 Output: 1 2 #1 3 # ExplanatFollow the steps below to solve the problem: Initialize a variable, say res, to store all possible shortest paths. Your task is to complete the function ShortestPath () which takes a string S and returns an array of strings containing the order of movements required to cover all characters of S. . from above to generate different subsequence. Here we not only find the shortest distance but also the path. where e is the number of edges in the graph. For Example, in the above binary tree the path between the nodes 7 and 4 is 7 -> 3 -> 1 -> 4 . of arr [] to temp [] 2) While temp [] contains more than one strings. Share. Auxiliary Space: O (R * C), as we are using extra space like visted [R] [C]. First you init the queue by all the positions of A in the grid. Example 2: Input: Output: 1 Explanation: The output 1 denotes that the order is valid. , whose minimum distance from source is calculated and finalized. Ini. For example, consider the below graph. You are given an Undirected Graph having unit weight, Find the shortest path from src to all the vertex and if. Let the src be 2 and dst be 3. Given a path in the form of a rectangular matrix having few. Here, for every vertex in the graph, we have a list of all the other vertices which the particular vertex has an edge to. Floyd Warshall. Complete the function shortest path () which takes a 2d vector or array edges representing the edges of undirected graph with unit weight, an integer N as number nodes, an integer. Algorithm: Steps involved in finding the topological ordering of a DAG: Step-1: Compute in-degree (number of incoming edges) for each of the vertex present in the DAG and initialize the count of visited nodes as 0.