Single Source Shortest Path (SSSP) refers to the problem of finding the shortest paths from a single source vertex to all other vertices in a weighted graph. In other words, given a graph where each edge has an associated weight or cost, the goal is to determine the minimum distance from a designated source vertex to every other vertex in the graph.

The problem can be formally defined as follows:

Given a weighted graph G=(V,E), where V is the set of vertices and E is the set of edges, and a source vertex s∈V, find the shortest path distance d(v) from s to every other vertex v∈V.

Time complexity-

Dijkstra's Algorithm

Dijkstra's algorithm is a greedy algorithm used to find the shortest paths from a single source vertex to all other vertices in a weighted, directed or undirected graph. It's particularly useful when the graph has non-negative edge weights. The algorithm maintains a set of vertices whose shortest distance from the source is known, and it iteratively selects the vertex with the smallest known distance, updates the distances of its neighbors, and continues until all vertices are processed.

Dijkstra's Algorithm Steps:

1. Initialization:

• Start with the source vertex.
• Set the distance of the source vertex to 0 and the distances of all other vertices to infinity.
• Maintain a priority queue (or a min-heap) to efficiently select the vertex with the smallest known distance.

2. Relaxation: