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New Exam Prep
An algorithm is a step-by-step procedure for solving a problem. Good algorithms are characterized by clarity, efficiency, and finiteness. Big-O, Big-âĻ, and Big-Î notations describe the upper, lower, and tight bounds of a...
Sample questions with model answers
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Explain Bubble Sort with an example and analyze its best-case and worst-case time complexity.
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Bubble Sort repeatedly swaps adjacent elements; best-case O(n), worst-case O(n^2).
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Explain Merge Sort using Divide and Conquer and derive its time complexity.
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Merge Sort divides the array, sorts subarrays, and merges; time complexity is O(n log n).
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Explain Selection Sort with a suitable example and analyze its time complexity.
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Selection Sort selects the minimum element; time complexity is O(n^2).
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Solve the recurrence relation of Merge Sort using the recursion tree method.
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The recurrence relation T(n) = 2T(n/2) + O(n) solves to T(n) = O(n log n).
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