Which of the following is not an application of depth first search?

By: Prof. Dr. Fazal Rehman | Last updated: February 3, 2024

Question:  Which of the following is not an application of depth first search?

A  For generating topological sort of a graph

B   For generating Strongly Connected Components of a directed graph

C  Detecting cycles in the graph

D  Peer to Peer Networks

Answer:   Peer to Peer Networks

 

Application of depth first search         Description
Topological Sorting ·        Ordering nodes in directed acyclic graphs (dags) to represent dependencies and scheduling tasks.
Cycle Detection ·        Identifying cycles in graphs

·        Useful for deadlock detection

·        Dependency analysis

·        Plagiarism detection

Graph Traversal ·        Traversing and searching through graphs

·        Finding paths cycles and connected components.

Maze Solving ·        Navigating through mazes and labyrinth puzzles to find a solution or determine an unsolvable path.
Pathfinding Algorithms ·        Finding optimal paths in robotics, video games and GPS navigation by exploring potential routes.
Strongly Connected Components (SCC) ·        Discovering SCCs in directed graphs

·        Valuable in model checking

·        Compiler optimizations and network analysis

Puzzle Solving ·        Solving puzzles like N-Queens

·        Sudoku and the Eight-Puzzle by searching through possible states and solutions.

Syntax Analysis in Compilers ·        Building abstract syntax trees (ASTs) from source code in compiler design for syntax analysis.
Web Crawling ·        Indexing web pages, collecting data and following links to explore websites for web crawling and web scraping.
Artificial Intelligence ·        Solving game trees

·        Planning and state space search in AI applications like chess, robotics and decision-making.

Biological Research ·        Applications in genome sequencing and phylogenetic tree construction

·        Protein structure prediction in computational biology

Network Routing ·        Determining efficient paths in computer networks for data packet routing and communication.
Natural Language Processing (NLP) ·        Parsing and analyzing natural language sentences for tasks like sentence parsing and part-of-speech tagging.

 

 

 

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