Graph traversal is a fundamental concept in computer science that involves exploring and visiting all the nodes or vertices of a graph data structure. Graphs are used to represent various realworld relationships and connections, and understanding how to traverse them is crucial for many applications.
Practically, graph traversal is used in a wide range of scenarios, such as:

Pathfinding and route planning: Graphs can represent transportation networks, such as roads, railways, or airline routes, and certain variations of graph traversal algorithms are used to find the shortest or most efficient paths between locations.

Social media networks: Graph traversal is used to analyze the connections between users, identify influential individuals, and recommend new connections.

Recommendation systems: Graphs can represent the relationships between products, users, and their preferences, allowing for personalized recommendations based on the user’s browsing history and the connections in the graph.

Web crawling and search engine optimization: Search engines use graph traversal techniques to explore and index the interconnected web pages, allowing for efficient information retrieval and ranking of search results.

Biological networks: Graphs can represent the interactions between genes, proteins, or other biological entities, and graph traversal is used to study and understand these complex networks.
Below are the major Graph Traversal Techniques: