graph terminology

Author: ZapDos7

README.md

@@ -126,11 +126,12 @@
 - [x] [Sort HashMap by value](https://www.digitalocean.com/community/tutorials/java-programming-interview-questions#24-write-a-java-program-that-sorts-hashmap-by-value)
 
 ### Graphs
+- [x] [Terminology and Representations of Graphs](http://www.techiedelight.com/terminology-and-representations-of-graphs/)
 - [x] Given a list of edges and tasked to build your own graph from the edges
 ### Matrix
 
 ### Trees
-- [ ] [Same Tree](https://leetcode.com/problems/same-tree/)
+- [x] [Same Tree](https://leetcode.com/problems/same-tree/)
 - [x] [Subtree of Another Tree](https://leetcode.com/problems/subtree-of-another-tree/)
 ### Heaps
 
@@ -281,7 +282,6 @@
     - [ ] [Graph Valid Tree](https://leetcode.com/problems/graph-valid-tree/)
     - [ ] [Number of Connected Components in an Undirected Graph](https://leetcode.com/problems/graph-valid-tree/)
     - [ ] [Longest Consecutive Sequence](https://leetcode.com/problems/longest-consecutive-sequence/)
-    - [ ] [Terminology and Representations of Graphs](http://www.techiedelight.com/terminology-and-representations-of-graphs/)
     - [ ] [Graph Implementation using STL](http://www.techiedelight.com/graph-implementation-using-stl/)
     - [ ] [Graph Implementation in C++ without using STL](http://www.techiedelight.com/graph-implementation-c-without-using-stl/)
     - [ ] [Arrival and Departure Time of Vertices in DFS](http://www.techiedelight.com/arrival-departure-time-vertices-dfs/)

src/dataStructures/graphs/graphs.md

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+## Graphs
+
+1. What is a Graph?
+ > A graph is an ordered pair G = (V, E) comprising a set V of vertices or nodes and a collection of pairs of vertices from V, known as edges of a graph. For example, for the graph below.
+ > V = { 1, 2, 3, 4, 5, 6 }E = { (1, 4), (1, 6), (2, 6), (4, 5), (5, 6) }
+  
+2. What Types of Graph are there?
+ > 1. Undirected graph (edges have no orientation - edges are not ordered pairs. The maximum number of edges possible in an undirected graph without a loop is n×(n-1)/2.)
+ > 2. Directed graph (edges have orientations, i.e., The edge (x, y) is not identical to edge (y, x).)
+ > 3. Directed Acyclic Graph (DAG) (A Directed Acyclic Graph (DAG) is a directed graph that contains no cycles.)
+ > 4. Multi graph (an undirected graph in which multiple edges (and sometimes loops) are allowed. Multiple edges are two or more edges that connect the same two vertices. A loop is an edge (directed or undirected) that connects a vertex to itself; it may be permitted or not.)
+ > 5. Simple graph (an undirected graph in which both multiple edges and loops are disallowed as opposed to a multigraph. In a simple graph with n vertices, every vertex’s degree is at most n-1.)
+ > 6. Weighted Graph (associates a value (weight) with every edge in the graph. We can also use words cost or length instead of weight.) - unweighted by default (aka weight = 1 everywhere)
+ > 7. Complete graph (A complete graph is one in which every two vertices are adjacent: all edges that could exist are present.)
+ > 8. Connected graph (has a path between every pair of vertices. In other words, there are no unreachable vertices. A disconnected graph is a graph that is not connected.)
+  
+[Further reading](https://www.techiedelight.com/terminology-and-representations-of-graphs/) 
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