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Merge pull request #218 from imVivekGupta/sort_doc

Updated doc for bfs dfs

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	`1`	`+## Breadth-first search (BFS)`
	`2`	`+ An algorithm for traversing or searching tree or graph data structures. It starts at the tree root (or some arbitrary node of a graph, sometimes referred to as a 'search key') and explores the neighbor nodes first, before moving to the next level neighbours.`
	`3`	`+`
	`4`	`+--------------------`
	`5`	`+![](https://upload.wikimedia.org/wikipedia/commons/4/46/Animated_BFS.gif)`
	`6`	`+`
	`7`	`+--------------------`
	`8`	`+This is the algorithm for Breadth First Search in a given graph.`
	`9`	`+`
	`10`	`+* We take a starting vertex , and push all its adjacent vertexes in a queue.`
	`11`	`+* Now we pop an element from a queue and push all its vertexes in the queue , and we also mark down these vertexes as visited.`
	`12`	`+* After executing the code, we will get the vertex visited in a breadth first manner.`
	`13`	`+`
	`14`	`+[More info](https://en.wikipedia.org/wiki/Breadth-first_search)`

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	`1`	`+## Depth-first search (DFS)`
	`2`	`+ An algorithm for traversing or searching tree or graph data structures. One starts at the root (selecting some arbitrary node as the root in the case of a graph) and explores as far as possible along each branch before backtracking`
	`3`	`+`
	`4`	`+----`
	`5`	`+![](https://upload.wikimedia.org/wikipedia/commons/7/7f/Depth-First-Search.gif)`
	`6`	`+----`
	`7`	`+This is the algorithm for Depth First Search in a given graph.`
	`8`	`+`
	`9`	`+* We take a starting vertex , and push all its adjacent vertexes in a stack.`
	`10`	`+* Now we pop an element from a stack and push all its vertexes in the stack , and we also mark down these vertexes as visited.`
	`11`	`+* After executing the code, we will get the vertex visited in a depth first manner.`
	`12`	`+`
	`13`	`+[more info](https://en.wikipedia.org/wiki/Depth-first_search)`

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	`1`	`+## Floyd–Warshall algorithm`
	`2`	`+An algorithm for finding shortest paths in a weighted graph with positive or negative edge weights (but with no negative cycles). A single execution of the algorithm will find the lengths (summed weights) of the shortest paths between all pairs of vertices.`
	`3`	`+`
	`4`	`+------------------------------`
	`5`	`+![](https://ds055uzetaobb.cloudfront.net/image_optimizer/bec3c44826d7cab9b828f339e4844b5a09df5fce.png)`
	`6`	`+`
	`7`	`+ ### Algorithm`
	`8`	`+`
	`9`	`+ If w(i,j) is the weight of the edge between`
	`10`	`+ vertices i and j, we can define shortestPath (i,j,k) in terms of the following recursive formula: the base case is shortestPath (i,j,0)=w(i,j) and the recursive case is shortestPath (i,j,k) = min( shortestPath (i,j,k-1), shortestPath (i,k,k-1)+ shortestPath (k,j,k-1)).`
	`11`	`+ This formula is the heart of the Floyd–Warshall algorithm. The algorithm works by first computing shortestPath (i,j,k) for all (i,j) pairs for k=1, then k=2, etc. This process continues until k=N, and we have found the shortest path for all (i,j) pairs using any intermediate vertices.`
	`12`	`+`
	`13`	`+----------------------------`
	`14`	`+### Performance Analysis`
	`15`	`+* Worst-case performance O(\|V\|^3)`
	`16`	`+* Best-case performance O(\|V\|^3)`
	`17`	`+* Average performance O(\|V\|^3)`

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