Virtual Labs

1. What is true about the time complexity of Kruskal's algorithm?

a: Best case is when given graph is a tree itself Explanation

Explanation

b: Worst case is when all edges are to be checked. Explanation

Explanation

c: Time complexity is O(E log(V) + E log(E)), where E is the number of edges and V is the number of Vertices Explanation

Explanation

d: All of the above Explanation

Explanation

2. Can Kruskal's algorithm produce more than one MST without any changes in the code?

a: Yes Explanation

Explanation

b: No Explanation

Explanation

c: Depends Explanation

Explanation

d: Can’t say Explanation

Explanation

3. What is the best case Time Complexity of Kruskal's Algorithm? (Let V be the number of vertices, E be the number of edges)

a: O((V-1)log(E)+Elog(E)) Explanation

Explanation

b: O(Vlog(E)+Elog(E)) Explanation

Explanation

c: O(Vlog(V)+Elog(E)) Explanation

Explanation

d: None of the above Explanation

Explanation

4. In which scenario, Kruskal’s algorithm will result in the best time complexity?

a: Maximum number of edges and maximum number of cycles Explanation

Explanation

b: Maximum number of edges and minimum number of cycles Explanation

Explanation

c: Minimum number of edges and maximum number of cycles Explanation

Explanation

d: Minimum number of edges and minimum number of cycles Explanation

Explanation

Minimum Spanning Trees