Introduction to Algorithms
3rd Edition
ISBN: 9780262033848
Author: Thomas H. Cormen, Ronald L. Rivest, Charles E. Leiserson, Clifford Stein
Publisher: MIT Press
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Given two sorted arrays A and B, design a linear
(O(IA|+|B|)) time algorithm for computing the set
C containing elements that are in A or B, but not
in both. That is, C = (AU B) \ (AN B). You can
assume that elements in A have different values
and elements in B also have different values.
Please state the steps of your algorithm clearly,
prove that it is correct, and analyze its running
time.
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Given an n-element array X of integers, Algorithm A executes an O(n3.4)-time computation for each even positive number in X, an Oin2.3-time computation for each odd positive
number in X, and an O(n2.5)-time computation for each negative number in X.
What are the best-case and worst-case running times of Algorithm A? Justify your answer.
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Chapter 15 Solutions
Introduction to Algorithms
Ch. 15.1 - Prob. 1ECh. 15.1 - Prob. 2ECh. 15.1 - Prob. 3ECh. 15.1 - Prob. 4ECh. 15.1 - Prob. 5ECh. 15.2 - Prob. 1ECh. 15.2 - Prob. 2ECh. 15.2 - Prob. 3ECh. 15.2 - Prob. 4ECh. 15.2 - Prob. 5E
Ch. 15.2 - Prob. 6ECh. 15.3 - Prob. 1ECh. 15.3 - Prob. 2ECh. 15.3 - Prob. 3ECh. 15.3 - Prob. 4ECh. 15.3 - Prob. 5ECh. 15.3 - Prob. 6ECh. 15.4 - Prob. 1ECh. 15.4 - Prob. 2ECh. 15.4 - Prob. 3ECh. 15.4 - Prob. 4ECh. 15.4 - Prob. 5ECh. 15.4 - Prob. 6ECh. 15.5 - Prob. 1ECh. 15.5 - Prob. 2ECh. 15.5 - Prob. 3ECh. 15.5 - Prob. 4ECh. 15 - Prob. 1PCh. 15 - Prob. 2PCh. 15 - Prob. 3PCh. 15 - Prob. 4PCh. 15 - Prob. 5PCh. 15 - Prob. 6PCh. 15 - Prob. 7PCh. 15 - Prob. 8PCh. 15 - Prob. 9PCh. 15 - Prob. 10PCh. 15 - Prob. 11PCh. 15 - Prob. 12P
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- Given an array A of n distinct positive integers and an integer B, find the number of unordered pairs of indices(i and j) such that i != j and that A[i] + A[j] > B using an algorithim in time nlogn. Prove that the algorithm you have is in time nlognarrow_forwardGiven an n-element sequence of integers, an algorithm executes an O(n)-time computation for each even number in the sequence, and an O(logn)-time computation for each odd number in the sequence. What are the best-case and worst-case running times of this algorithm? Why? Show with proper notations.arrow_forwardComputer Science Write the PSEUDOCODE for an algorithm that takes as input a list of numbers that are sorted in nondecreasing order, and finds the location(s) of the most frequently occurring element(s) in the list. If there are more than one element that is the most frequently occurring, then return the locations of all of them. Analyze the worst-case time complexity of this algorithm and give the O() estimate. (A list is in nondecreasing order if each number in the list is greater than or equal to the number preceding it.)arrow_forward
- Give an O.n lg n/-time algorithm to find the longest monotonically increasing subsequence of a sequence of n numbers. (Hint: Observe that the last element of a candidate subsequence of length i is at least as large as the last element of a candidate subsequence of length i 1. Maintain candidate subsequences by linking them through the input sequence.)arrow_forwardThe median m of a sequence of n elements is the element that would fall in the middle if the sequence was sorted. That is, e ≤ m for half the elements, and m ≤ e for the others. Clearly, one can obtain the median by sorting the sequence, but one can do quite a bit better with the following algorithm that finds the kth element of a sequence between a (inclusive) and b (exclusive). (For the median, use k = n/2, a = 0, and b = n.) select(k, a, b)Pick a pivot p in the subsequence between a and b.Partition the subsequence elements into three subsequences: the elements <p, =p, >p Let n1, n2, n3 be the sizes of each of these subsequences.if k < n1 return select(k, 0, n1).else if (k > n1 + n2) return select(k, n1 + n2, n).else return p. c++arrow_forwardLet S = (a1a2,...an) be a sequence of integers. Design an algorithm to find the subsequence SM = (ai,ai+1,...,aj) of S, with consecutive elements, such that the sum of the numbers in SM is maximum over all subsequences of S. Note that the sum is assumed to be 0 if the subsequence is empty. Your algorithm should run in O(n) time.arrow_forward
- Given a sorted array of n comparable items A, and a search value key, return the position (array index) of key in A if it is present, or -1 if it is not present. If key is present in A, your algorithm must run in order O(log k) time, where k is the location of key in A. Otherwise, if key is not present, your algorithm must run in O(log n) time.arrow_forwardGiven a set S of n planar points, construct an efficient algorithm to determine whether or not there exist three points in S that are collinear. Hint: While there are Θ(n3) triples of members of S, you should be able to construct an algorithm that runs in o(n3) sequential time.arrow_forward2. Expand the following recurrence to help you find a closed-form solution, and then use induction to prove your answer is correct. T(n) = T(n-1) + 5 for n> 0; T(0) = 8. 3. Give a recursive algorithm for the sequential search and explain its running time.arrow_forward
- Consider a function f: N → N that represents the amount of work done by some algorithm as follow: f(n) = {(1 if n is oddn if n is even)┤ Prove or disprove. f(n) is O(n). Please show proof or disproofarrow_forwardProvide a most efficient divide-and-conquer algorithm for determining the smallest and second smallest values in a given unordered set of numbers. Provide a recurrence equation expressing the time complexity of the algorithm, and derive its exact solution in the number of comparisons. For simplicity, you may assume the size of the problem to be an exact power of a the number 2arrow_forwardGiven a linked list L storing n integers, present an algorithm (either in words or in a pseudocode) that decides whether L contains any 0 or not. The output of your algorithm should be either Yes or No. What is the running time of your algorithm in the worst-case, using O notation?arrow_forward
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