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Consider the following algorithm to check whether a graph defined by itsadjacency matrix is complete.ALGORITHM GraphComplete(A[0..n − 1, 0..n − 1])//Input: Adjacency matrix A[0..n − 1, 0..n − 1]) of an undirected graph G//Output: 1 (true) if G is complete and 0 (false) otherwiseif n = 1 return 1 //one-vertex graph is complete by definitionelseif not GraphComplete(A[0..n − 2, 0..n − 2]) return 0else for j ← 0 to n − 2 doif A[n − 1, j ] = 0 return 0return 1What is the algorithm’s efficiency class in the worst case?

Question

Consider the following algorithm to check whether a graph defined by itsadjacency matrix is complete.ALGORITHM GraphComplete(A[0..n − 1, 0..n − 1])//Input: Adjacency matrix A[0..n − 1, 0..n − 1]) of an undirected graph G//Output: 1 (true) if G is complete and 0 (false) otherwiseif n = 1 return 1 //one-vertex graph is complete by definitionelseif not GraphComplete(A[0..n − 2, 0..n − 2]) return 0else for j ← 0 to n − 2 doif A[n − 1, j ] = 0 return 0return 1What is the algorithm’s efficiency class in the worst case?

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Solution

The efficiency class of the given algorithm in the worst case is O(n^2). This is because the algorithm checks each element in the adjacency matrix once, and the adjacency matrix has n^2 elements (where n is the number of vertices in the graph). Therefore, the time complexity of the algorithm is proportional to the square of the size of the input, which is characteristic of the O(n^2) complexity class.

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