![]() append ( w )īoth of these have the property that replacing the stack by a queue gives a breadth-first search, implemented in a somewhat nonstandard way. This is the approach taken by Kleinberg and Tardos's Algorithm Design:ĭef dfs2 ( G, s ): visited = set () stack = while stack : v = stack. pop ()Īlternatively, you can push all neighbors and delay the check for whether a vertex has been visited until it is popped. append ( iter ( G )) except StopIteration : stack. Here's what you get if you swap a stack for the queue in breadth first search: def stack_traversal ( G, s ): visited = stack = )] while stack : try : w = stack. Embarrassingly, the Wikipedia depth first search article made the same mistake (until today), as do some textbooks (for example Skiena's Algorithm Design Manual p. 169 Jeff Edmonds' How to Think about Algorithms, pp. 175–178 Gilberg and Forouzan Data Structures: A Pseudocode Approach Using C, 2nd ed., p. 497). We need int** to store a two dimensional array.I just finished teaching our required undergraduate algorithms class, and in grading their final exams I discovered that a few of the students have (not from me) acquired the incorrect belief that modifying the standard version of the breadth first search algorithm by replacing the stack with a queue makes it into depth first search. The code has been simplified so that we can focus on the algorithm rather than other details. The code for the Depth First Search Algorithm with an example is shown below. This is because the graph might have two different disconnected parts so to make sure that we cover every vertex, we can also run the DFS algorithm on every node.ĭFS Implementation in Python, Java and C/C++ In the init() function, notice that we run the DFS function on every node. After we visit the last element 3, it doesn't have any unvisited adjacent nodes, so we have completed the Depth First Traversal of the graph.ĭFS Pseudocode (recursive implementation) Vertex 2 has an unvisited adjacent vertex in 4, so we add that to the top of the stack and visit it.Īfter we visit the last element 3, it doesn't have any unvisited adjacent nodes, so we have completed the Depth First Traversal of the graph. Vertex 2 has an unvisited adjacent vertex in 4, so we add that to the top of the stack and visit it. Since 0 has already been visited, we visit 2 instead. ![]() Next, we visit the element at the top of stack i.e. Visit the element and put it in the visited list We start from vertex 0, the DFS algorithm starts by putting it in the Visited list and putting all its adjacent vertices in the stack. We use an undirected graph with 5 vertices. Let's see how the Depth First Search algorithm works with an example.
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