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The total of time needed by an algorithm to run to its completion is termed as time complexity. The asymptotic running time of an algorithm is given in terms of functions. The upper bound for a function 'f' is provided by the big oh notation (O). Taking 'g' to be a function from the non-negative integers to the positive real numbers, we define O(g) as a set of function f such that for some real constant c>0 and for some non negative integers constant n0, f(n)≤cg(n) for all n≥n0. Mathematically, O(g(n))={f(n): there are positive constants such that 0≤f f(n)≤cg(n) for all n, n≥n0} , we say "f is oh of g"
Q. Explain the term hashing? Explain any five well known hash functions. Ans: Hashing method provides us the direct access of record from the f
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Best Case: If the list is sorted already then A[i] T (n) = c1n + c2 (n -1) + c3(n -1) + c4 (n -1) = O (n), which indicates that the time complexity is linear. Worst Case:
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Q. Write down the binary search algorithm and trace to search element 91 in following given list: 13 30 62 73 81 88 91
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