Introduction
This post about Bellman Ford Algorithm is a continuation of the post Shortest Path Using Dijkstra's Algorithm. While learning about the Dijkstra's way, we learnt that it is really efficient an algorithm to find the single source shortest path in any graph provided it has no negative weight edges and no negative weight cycles.
The running time of the Dijkstra's Algorithm is also promising, O(E +VlogV) depending on our choice of data structure to implement the required Priority Queue.
Why Bellman Ford Algorithm?
There can be scenarios where a graph may contain negative weight ...

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# Graph Theory

This category is the parent of all articles which have mention of Graphs and Graph related problems.

## Further Reading for Minimum Spanning Tree

Introduction
This is a supplement to the posts for Minimum Spanning Tree and their Analysis. Check out the other related articles in the following section.
Further Reading for Minimum Spanning Tree
This section is meant to be read in conjunction to the post Minimum Spanning Tree - Prim's Algorithm
The minimum spanning tree of a Graph is the union of minimum spanning trees of its connected components.
This is a very important observation and it must be discussed in length and breadth because this will help us design our algorithm for MST in a
better way.
Why is it so important to underst...

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## Minimum Spanning Tree Prim’s Algorithm

Introduction
What is the minimum length of the network cable we require if we have to connect 100 computing machines in a building distributed across multiple floors? How do I guarantee that there can be no other minimum length possible than what I derive? Why is it even important to find the minimum length?
The history of the problem
You can read the classic problem solved by MST Applications of Minimum Spanning Tree
Defining Spanning Trees
A spanning tree is always defined for a weighted Graph G(V,E) where the weights are positive. This means that all the edges carry some positive we...

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## Shortest Path using Dijkstra’s Algorithm

Introduction
This is the third post in the Graph Traversals – Online Classes.
After learning how to move through a graph, we might be interested in learning more. One interesting problem is determining the shortest path between two vertices of a graph.
The problem can be extended and defined in many other forms. I prefer to call it "minimizing the cost". For e.g.
When we measure the cost in terms of the distances between vertices, it can be called as the Shortest Path.
When we measure the cost in terms of the money spent between vertices, it can be called as the Cheapest Path.
Whe...

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## Depth First Traversal

Introduction
This is the second post in the Graph Traversals – Online Classes.
I Recommend you to look at the first post Breadth First Traversal as it contains more explanation and details and I will keep this post smaller just around the depth first concept.
Depth First Traversal
The Idea
In this traversal, we choose a start vertex and keep moving forward along the length of the graph until there is no undiscovered vertex in that path. Once reaching a dead end, we back track to all the visited vertices and check if we have any vertex which has an adjacent undiscovered vertex.
We kee...

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