W = x; if (m > 0) // node 1 { W++; // node 2 } else { w=2*w; // node 3 } //node 4 (no executable statement) if (y <= 10) { x = 5*y; // node 5 } else { x=3y+5; //node 6 } z = W + x; // node 7

The following is a graph theory problem: Suppose we have a graph A = (X, Y) and a subgraph of A, which is expressed as B = (x, y). x is an element of X and y is an element of Y. A subgraph is plainly described as a graph obtained from A by removing vertices &/or edges. For every following statement determine whether it is true or false. Explain or provide counterexample. Be careful when answering the following questions to leave edges that have their endpoints in B.  (i) If A is connected then B is connected (and vice versa: If B... then A) (ii)  If A is simple graph then B is simple graph (and vice versa: If B... then A) (iii) If A contains a cycle then B contains a cycle (and vice versa: If B... then A) (iv) If A is a tree then B is a tree (and vice versa: If B... then A)

Can you use DFS to assess if two graphs are related? If you can find it, step-by-step instructions are given.

Please explain Some engineers at Google want you to implement a graph structure of the subway system in Boston showing the connections between each station.They are wondering what data structure to use to represent the graph and use the least amount of memory, given that most stations do not connect to many other stations. Which graph data structure representation should you use and why? Group of answer choices a.  Adjacency List -- Because the complexity is O(V+E), the data structure is better at representing sparse graphs since their are fewer connections.   b. Adjacency Matrix -- Because the complexity is O(V+E), the data structure is better at representing sparse graphs since their are fewer connections.