Time complexity of kruskal using array data structure
Here is the original question encountered by the OP, quoted here so that readers do not have to register to that website just to take a look at the question.


  Consider a graph with V vertices and e edges,What is the worst case time complexity for kruskal's algorithm when implemented using array data structure?
  a.) E+ElogV
  b.)VlogV
  c.)V^2
  d.)Vlog^2V


The only correct answer as I see is, the original question is ill-posed. It is ill-posed because of its unconventional, ambiguous, almost meaningless use of "using array data structure".

Array is such a fundamental data structure, it usually converys little information when you say an algorithm is implemented using array data structure. Especially in the current case of Kruskal's algorithm, we usually refer to the disjoint-set data structure used in the algorithm to keep track of which vertices are in which connected components and to determine whether an edge will join two different connected components. In fact, the whole page about Kruskal's algorithm in wikipedia does not mention "array" even once. Although well versed regarding to minimal spanning tree and Kruskal's algorithm[1], I am confused by this "using array data structure".

Let us also take a look at other aspects of the original question. It has bad capitalization, bad punctuation, and inconsistent white spacing. It introduces "$e$ edges" but use $E$ in the choices. When it lists the time complexities, it should apply the big $O$ notation such as $O(E+E\log V)$. It skips the basic description of the graph as connected edge-weighted.  

All in all, it is fair to say the original question is of such a low quality, you should just ignore it. Try not to learn from it.