Warning: foreach() argument must be of type array|object, bool given in /var/www/html/web/app/themes/studypress-core-theme/template-parts/header/mobile-offcanvas.php on line 20

Either prove or give a counterexample: if {u,v}is an edge in an undirected graph, and during depth-first search (u)<post (v), then vis an ancestor of uin the DFS tree.

Short Answer

Expert verified

If {u,v} is an edge in an undirected graph, and during the depth-first search post (u) < post(v) , then v is an ancestor of u in the DFS tree.

Step by step solution

01

Depth-first search

Depth First Search (DFS) is an application of graph traversal. It traverses the node downwards and uses the stack as a data structure through this it traverses all vertices in the downward direction one by one.

Some properties ofdepth-first search are as follows:

  1. Using DFT we can verify whether the graph is connected or not it means it detects the cycle present in the graph or not.
  2. We can find out the number of connected components by using adepth-first search.
  3. Here we are using the stack as a data structure.

The time complexity of the list is O(V+E).

The time complexity of matrix isOV2.

It contains various edges, they aretree edge, forward edge, back edge, or cross edge all the edges are explained below:

Tree edge: The graph obtained by traversing while using a depth-first search is called its tree edge.

Forward edge: the edge {u,v} whereis a descendant and it is not part of the depth-first search is called the forward edge.

Back edge: the edge {u,v} where is the ancestor and it is not part of the depth-first search is called the back edge.

02

Step 2: During DFS,post (u) < (v) , and v is an ancestor of u in the DFS tree

Consider the depth first search tree of graph G starting at any vertex. For this graph, if depth-first search is performed in the graph then if post is less than post v than, here the edge {u,v} where u is ancestor and it is not part of depth first search is called back edge. If {u,v} is an edge in an undirected graph and while performing a depth-first search in the undirected connected graph the the post (u)< post (v) , then v is an ancestor of in the DFS tree.

Here it follows these two conditions:

  1. [preu,post u] [prev.post v ]
  2. [prev,[preu,post u]post v ]

Only these options are taking place here for an undirected graph post u is less than post v. since there is an edge between these two vertices and option one is not possible because it is a must to traverse all the neighbors of a vertex before marking it as visited.

So, option twoโ€™s condition is only possible which defines the vertex v is the ancestor of u. hence an undirected graph, and during the depth-first search, post(u) < post (v),then v is an ancestor of u in the depth-first search traversal.

Unlock Step-by-Step Solutions & Ace Your Exams!

  • Full Textbook Solutions

    Get detailed explanations and key concepts

  • Unlimited Al creation

    Al flashcards, explanations, exams and more...

  • Ads-free access

    To over 500 millions flashcards

  • Money-back guarantee

    We refund you if you fail your exam.

Over 30 million students worldwide already upgrade their learning with Vaia!

One App. One Place for Learning.

All the tools & learning materials you need for study success - in one app.

Get started for free

Most popular questions from this chapter

Rewrite the explore procedure (Figure 3.3) so that it is non-recursive (that is, explicitly use a stack). The calls to pre visit and post visit should be positioned so that they have the same effect as in the recursive procedure.

Suppose a CS curriculum consists of n courses, all of them mandatory. The prerequisite graph G has a node for each course, and an edge from course v to course w if and only if v is a prerequisite for w. Find an algorithm that works directly with this graph representation, and computes the minimum number of semesters necessary to complete the curriculum (assume that a student can take any number of courses in one semester). The running time of your algorithm should be linear.

You are given a directed graph in which each nodeuโˆˆV, has an associated pricepu which is a positive integer. Define the array cost as follows: for each uโˆˆV,

cost[u] = price of the cheapest node reachable fromu (includingu itself).

For instance, in the graph below (with prices shown for each vertex), the cost values of the nodes A,B,C,D,E,Fare2,1,4,1,4,5,respectively.

Your goal is to design an algorithm that fills in the entire cost array (i.e., for all vertices).

(a) Give a linear-time algorithm that works for directed acyclic graphs.

(b) Extend this to a linear-time algorithm that works for all directed graphs.

Perform depth-first search on each of the following graphs; whenever thereโ€™s a choice of vertices, pick the one that is alphabetically first. Classify each edge as a tree edge, forward edge, back edge, or cross edge, and give the pre and post number of each vertex.

Pouring water.

We have three containers whose sizes are 10 pints, 7 pints, and 4 pints, respectively. The 7-pint and 4-pint containers start out full of water, but the 10-pint container is initially empty. We are allowed one type of operation: pouring the contents of one container into another, stopping only when the source container is empty or the destination container is full. We want to know if there is a sequence of pouringโ€™s that leaves exactly 2 pints in the 7- or 4-pint container.

(a) Model this as a graph problem: give a precise definition of the graph involved and state the specific question about this graph that needs to be answered.

(b) What algorithm should be applied to solve the problem?

(c) Find the answer by applying the algorithm.

See all solutions

Recommended explanations on Computer Science Textbooks

View all explanations

What do you think about this solution?

We value your feedback to improve our textbook solutions.

Study anywhere. Anytime. Across all devices.

Sign-up for free