- Data Structures & Algorithms
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- Graph Data Structure
- DSA - Graph Data Structure
- DSA - Depth First Traversal
- DSA - Breadth First Traversal

- Tree Data Structure
- DSA - Tree Data Structure
- DSA - Tree Traversal
- DSA - Binary Search Tree
- DSA - AVL Tree
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# Data Structure & Algorithms - Spanning Tree

A spanning tree is a subset of Graph G, which has all the vertices covered with minimum possible number of edges. Hence, a spanning tree does not have cycles and it cannot be disconnected..

By this definition, we can draw a conclusion that every connected and undirected Graph G has at least one spanning tree. A disconnected graph does not have any spanning tree, as it cannot be spanned to all its vertices.

We found three spanning trees off one complete graph. A complete undirected graph can have maximum **n ^{n-2}** number of spanning trees, where

**n**is the number of nodes. In the above addressed example,

**n is 3,**hence

**3**spanning trees are possible.

^{3−2}= 3## General Properties of Spanning Tree

We now understand that one graph can have more than one spanning tree. Following are a few properties of the spanning tree connected to graph G −

A connected graph G can have more than one spanning tree.

All possible spanning trees of graph G, have the same number of edges and vertices.

The spanning tree does not have any cycle (loops).

Removing one edge from the spanning tree will make the graph disconnected, i.e. the spanning tree is

**minimally connected**.Adding one edge to the spanning tree will create a circuit or loop, i.e. the spanning tree is

**maximally acyclic**.

## Mathematical Properties of Spanning Tree

Spanning tree has

**n-1**edges, where**n**is the number of nodes (vertices).From a complete graph, by removing maximum

**e - n + 1**edges, we can construct a spanning tree.A complete graph can have maximum

**n**number of spanning trees.^{n-2}

Thus, we can conclude that spanning trees are a subset of connected Graph G and disconnected graphs do not have spanning tree.

## Application of Spanning Tree

Spanning tree is basically used to find a minimum path to connect all nodes in a graph. Common application of spanning trees are −

**Civil Network Planning****Computer Network Routing Protocol****Cluster Analysis**

Let us understand this through a small example. Consider, city network as a huge graph and now plans to deploy telephone lines in such a way that in minimum lines we can connect to all city nodes. This is where the spanning tree comes into picture.

## Minimum Spanning Tree (MST)

In a weighted graph, a minimum spanning tree is a spanning tree that has minimum weight than all other spanning trees of the same graph. In real-world situations, this weight can be measured as distance, congestion, traffic load or any arbitrary value denoted to the edges.

## Minimum Spanning-Tree Algorithm

We shall learn about two most important spanning tree algorithms here −

Both are greedy algorithms.