A graph is a type of non-linear data structure. A graph is defined as a group of vertices, and edges are used to connect these vertices. There are many different types of graphs, such as directed, undirected, weighted, unweighted, cyclic, acyclic, etc. There are many real-life applications of the graph. They are used in maps, social media, path optimization algorithms, etc.
A graph is an ADT, here ADT refers to the Abstract Data Type, and it can be used to represent non-linear relationships and complex relationships between objects. A graph consists of nodes commonly known as vertices, that are connected by edges. Graphs have a lot of key terms: When an edge connects two nodes, they are called neighbors. In this, we have covered all the classic problems related to graphs. Basically starting from graph traversals and gradually increasing the level by discussing all the classic problems.
The advanced topics under Graph Data Structure include traversable and Euclidean graphs, isomorphic and homogeneous graphs, fuzzy graphs, etc. Questions from these topics might be asked in the Technical Interviews of Product-Based Companies.
Advanced graph concepts can seem tricky at first. But after getting a good understanding, they can get easier. Let us try to solve some mixed problems on advanced graph theory concepts to deepen our understanding.
Top Problems related to Graph
Colour The Graph
Properties of MST in a Undirected Graph
Detect Cycle in a Undirected Graph
Minimum Time in Wormhole Network
Minimum Spanning Tree
Detect Cycle in an Undirected Graph
Bridges In A Graph
Minimum steps to reach target by a Knight
Dijkstra's shortest path
Check If Path Exists
Number Of Triangles In An Undirected Graph
Detect Cycle in a Directed Graph