Consider the following snippet of pseudocode that takes as input an array of n integers. 1:...

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Consider the following snippet of pseudocode that takes as input an array of n integers. 1: function algorithm(A) 2: n + length of A 3: num_matches +0 4: for i in [0: n] do ▷ i ranges from 0 to n - 1 5: for j in [i + 1:n] do ▷ j ranges from i + 1 ton-1 6: if A[i] = =A[j] then 7: num_matches + num_matches + 1 8: return num_matches Your task is to: 1) upperbound the running time of the algorithm in terms of n using Onotation. 2) lowerbound the running time of the algorithm in terms of n Using notation. Consider the following snippet of pseudocode that takes as input an array of n integers. 1: function algorithm(A) 2: n + length of A 3: num_matches +0 4: for i in [0: n] do ▷ i ranges from 0 to n - 1 5: for j in [i + 1:n] do ▷ j ranges from i + 1 ton-1 6: if A[i] = =A[j] then 7: num_matches + num_matches + 1 8: return num_matches Your task is to: 1) upperbound the running time of the algorithm in terms of n using Onotation. 2) lowerbound the running time of the algorithm in terms of n Using notation.

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Answer 1 Upperbound the running time of the algorithm in terms of n using Big O notation In the give... View the full answer