Explain the following transitions with respect to an NGN network. Some computer scientists like to think of the number of bits in a computer word as being (lg n). Radix sorting by the least-significant digit first appears to be a folk algorithm widely used by operators of mechanical card-sorting machines. Figure 9.4 The operation of BUCKET-SORT. Figure 9.4 The operation of BUCKET-SORT. 2 for i 1 to n 657 436 436 436 Conclude that d(k) = (k lg k). There are d passes, so the total time for radix sort is (dn + kd). Thus, when primary memory storage is at a premium, an algorithm such as quicksort may be preferable. for TA, and conclude that the expected time to sort n elements is (n lg n). (a) The array A and the auxiliary array C after line 4. 9.2-5 BUCKET-SORT(A) Show how to sort n integers in the range 1 to n2 in O(n) time. b. The input sequence consists of n/k subsequences, each containing k elements. asked Jun 28, 2019 in Algorithms akash.dinkar12 60 views. Bucket sort runs in linear time on the average. Which of the following sorting algorithms are stable: insertion sort, merge sort, heapsort, and quicksort? 5 do sort list B[i] with insertion sort 9.1-5 9] of sorted lists (buckets) after line 5 of the algorithm. The probability that a given element falls into bucket B[i] is 1/n, since each bucket is responsible for 1/n of the interval [0,1). In a typical computer, which is a sequential random-access machine, radix sort is sometimes used to sort records of information that are keyed by multiple fields. (See Section 6.2 for a definition of uniform distribution.) The total time to examine all buckets in line 5 is O(n), and so the only interesting part of the analysis is the time taken by the insertion sorts in line 5. Exercises The code requires an auxiliary array B[0..n - 1] of linked lists (buckets) and assumes that there is a mechanism for maintaining such lists. How much time does counting sort require? 1 n length [A] lg(n!)) . Then, if each number to be sorted fits in one computer word, we can treat it as a d-digit number in radix-n notation. Now, consider a randomized comparison sort B. After the initialization in lines 1-2, we inspect each input element in lines 3-4. According to Knuth, the first published reference to the method is a 1929 document by L. J. Comrie describing punched-card equipment. Then, if each number to be sorted fits in one computer word, we can treat it as a d-digit number in radix-n notation. When each digit is in the range 1 to k, and k is not too large, counting sort is the obvious choice. When the lists of B are concatenated in line 6, elements of bucket B[i'] come before elements of B[j'], and thus A[i] precedes A[j] in the output sequence. It is a non-comparison based sorting algorithm that sorts a collection of integers. (The other two places are used for encoding nonnumeric characters.) Unfortunately, the version of radix sort that uses counting sort as the intermediate stable sort does not sort in place, which many of the (n lg n) comparison sorts do. Thus, bucket sort works. = j', An operator can then gather the cards bin by bin, so that cards with the first place punched are on top of cards with the second place punched, and so on. (b) The array C after line 7. Give a simple, linear-time algorithm for sorting the n data records in place. The following procedure assumes that each element in the n-element array A has d digits, where digit 1 is the lowest-order digit and digit d is the highest-order digit. = j', A decision tree represents the comparisons performed by a sorting algorithm when it operates on an input of a given size. This scheme must be modified slightly to handle the situation in which several elements have the same value, since we don't want to put them all in the same position. Thus, the situation is analogous to the ball-tossing example of Section 6.6.2: we have n balls (elements) and n bins (buckets), and each ball is thrown independently with probability p = 1 /n of falling into any particular bucket. c. Let d(m) be the minimum value of D(T) over all trees T with m leaves. Bucket i holds values in the interval [i/10,(i + 1)/10). 5 do sort list B[i] with insertion sort .10]. Thus, the entire bucket sort algorithm runs in linear expected time. 9.3-5 which is a contradiction, since i' < j'. Unfortunately, since the cards in 9 of the 10 bins must be put aside to sort each of the bins, this procedure generates many intermediate piles of cards that must be kept track of. Use no storage of more than constant size in addition to the storage provided by the array. 4 for i 0 to n -1 b. There are d passes, so the total time for radix sort is (dn + kd). The correctness of radix sort follows by induction on the column being sorted (see Exercise 9.3-3). A d-digit number would then occupy a field of d columns. Thoughts on parallelizing the counting sort … Give a simple scheme that makes any sorting algorithm stable. a. The total expected time to sort all the elements in all the buckets is therefore, In order to evaluate this summation, we must determine the distribution of each random variable ni. The vertical arrows indicate the digit position sorted on to produce each list from the previous one. and that the rest are labeled 0. Only the lightly shaded elements of array B have been filled in. Use no storage of more than constant size in addition to the storage provided by the array. Since the card sorter can look at only one column at a time, the problem of sorting n cards on a d-digit number requires a sorting algorithm. . Show how to sort the numbers in linear expected time. n] holds the sorted output, and the array C[1 . Since a binary tree of height h has no more than 2h leaves, we have 8], where each element ofA is a positive integer no larger than k = 6. Now, consider a randomized comparison sort B. Counting sort assumes that each of the n input elements is an integer in the range 1 to k, for some integer k. When k = O(n), the sort runs in O(n) time. For example, we might wish to sort dates by three keys: year, month, and day. 839 457 839 457 Thus, when primary memory storage is at a premium, an algorithm such as quicksort may be preferable. What is the smallest possible depth of a leaf in a decision tree for a sorting algorithm? Conclude that d(k) = (k lg k). Prove that exactly n! Suppose that each leaf of TA is labeled with the probability that it is reached given a random input. Knuth credits H. H. Seward with inventing counting sort in 1954, and also with the idea of combining counting sort with radix sort. In a typical computer, which is a sequential random-access machine, radix sort is sometimes used to sort records of information that are keyed by multiple fields. We are given n points in the unit circle, pi = (xi, yi), such that . Your algorithm should use O(n + k) preprocessing time. Lower bounds for sorting using generalizations of the decision-tree model were studied comprehensively by Ben-Or [23]. Give a simple, linear-time algorithm for sorting the n data records in place. BUCKET-SORT(A) Unfortunately, the version of radix sort that uses counting sort as the intermediate stable sort does not sort in place, which many of the (n lg n) comparison sorts do. for TA, and conclude that the expected time to sort n elements is (n lg n). (See Section 6.2 for a definition of uniform distribution.) Like counting sort, bucket sort is fast because it assumes something about the input. .10]. Prove that COUNTING-SORT is stable. Is counting sort stable and online? .10]. Theorem 9.1 The decision-tree model for studying comparison sorts was introduced by Ford and Johnson [72]. We can extend the decision-tree model to handle randomization by incorporating two kinds of nodes: ordinary comparison nodes and "randomization" nodes. 9.2-5 The total time to examine all buckets in line 5 is O(n), and so the only interesting part of the analysis is the time taken by the insertion sorts in line 5. 9.4-1 Prove That COUNTING-SORT Is Stable. Bucket i holds values in the interval [i/10,(i + 1)/10). 9.4-2 and that the rest are labeled 0. Whereas counting sort assumes that the input consists of integers in a small range, bucket sort assumes that the input is generated by a random process that distributes elements uniformly over the interval [0,1). Let i be the number of leaves in RT and k - i the number of leaves in LT.) 9.3-1 Show that d(k) = min1ik {d (i)+d(k - i)+k}. In a typical computer, which is a sequential random-access machine, radix sort is sometimes used to sort records of information that are keyed by multiple fields. Prove that 2n - 1 comparisons are necessary in the worst case to merge two sorted lists containing n elements each. Bucket sort runs in linear time on the average. How many piles of cards would an operator need to keep track of in the worst case? The remaining columns show the list after successive sorts on increasingly significant digit positions. and that the rest are labeled 0. Thus, bucket sort works. Conclude that d(k) = (k lg k). Show that d(k) = min1ik {d (i)+d(k - i)+k}. Thus, bucket sort works. We assume that every permutation of A's inputs is equally likely. Bucket sort runs in linear time on the average. Can your sort from part (a) be used to radix sort n records with b-bit keys in O(bn) time? A randomization node models a random choice of the form RANDOM( 1, r) made by algorithm B; the node has r children, each of which is equally likely to be chosen during an execution of the algorithm. We begin by examining a deterministic comparison sort A with decision tree TA. 6 concatenate the lists B[0], B[1], . To see that this algorithm works, consider two elements A[i] and A[j]. Conclude that d(k) = (k lg k). . 355 839 657 839 . The vertical arrows indicate the digit position sorted on to produce each list from the previous one. = j', Knuth's comprehensive treatise on sorting [123] covers many variations on the sorting problem, including the information- theoretic lower bound on the complexity of sorting given here. Hence, we must show that A[i] A[j]. For decimal digits, only 10 places are used in each column. Thus, the situation is analogous to the ball-tossing example of Section 6.6.2: we have n balls (elements) and n bins (buckets), and each ball is thrown independently with probability p = 1 /n of falling into any particular bucket. From Stirling's approximation (2.11), we have Go to Chapter 10     Back to Table of Contents. 5 do sort list B[i] with insertion sort Go to Chapter 10     Back to Table of Contents, 9.4-4 Use induction to prove that radix sort works. Show how to sort the numbers in linear expected time. Counting sort is illustrated in Figure 9.2. 9.4-4 Consequently, the worst-case number of comparisons for a comparison sort corresponds to the height of its decision tree. The elements in a given subsequence are all smaller than the elements in the succeeding subsequence and larger than the elements in the preceding subsequence. Suppose that the points are uniformly distributed; that is, the probability of finding a point in any region of the circle is proportional to the area of that region. You may use O(k) storage outside the input array. ,(n). and that the rest are labeled 0. Show that the algorithm still works properly. Knuth's comprehensive treatise on sorting [123] covers many variations on the sorting problem, including the information- theoretic lower bound on the complexity of sorting given here. = j', 9.3-5 For example, if there are 17 elements less than x, then x belongs in output position 18. Unfortunately, the version of radix sort that uses counting sort as the intermediate stable sort does not sort in place, which many of the (n lg n) comparison sorts do. c. Suppose that the n records have keys in the range from 1 to k. Show how to modify counting sort so that the records can be sorted in place in O(n + k) time. . (9.1) c. Let d(m) be the minimum value of D(T) over all trees T with m leaves. Can your sort from part (a) be used to radix sort n records with b-bit keys in O(bn) time? The analysis of the running time depends on the stable sort used as the intermediate sorting algorithm. Lower bounds for sorting using generalizations of the decision-tree model were studied comprehensively by Ben-Or [23]. Our code for bucket sort assumes that the input is an n-element array A and that each element A[i] in the array satisfies 0 A[i] < 1. 9.4 Bucket sort In a decision tree, each internal node is annotated by ai : aj for some i and j in the range 1 i, j n, where n is the number of elements in the input sequence. Bucket sort runs in linear time on the average. 9.2-4 (Hint: Consider a tree T with k leaves that achieves the minimum. Since insertion sort runs in quadratic time (see Section 1.2), the expected time to sort the elements in bucket . Bucket i holds values in the interval [i/10,(i + 1)/10). Suppose that the for loop in line 9 of the COUNTING-SORT procedure is rewritten: (The other two places are used for encoding nonnumeric characters.) How much additional time and space does your scheme entail? . Alternatively, we could sort the information three times with a stable sort: first on day, next on month, and finally on year. Then, if each number to be sorted fits in one computer word, we can treat it as a d-digit number in radix-n notation. Where does your proof need the assumption that the intermediate sort is stable? 9.4-3 and that the rest are labeled 0. 5 do sort list B[i] with insertion sort Problems 9.2-4 Show that there is no comparison sort whose running time is linear for at least half of the n! Let i be the number of leaves in RT and k - i the number of leaves in LT.) (Hint: How would you do it for k = 3?) = j', Suppose that the for loop in line 9 of the COUNTING-SORT procedure is rewritten: nA[j] permutations of n elements, each permutation representing a distinct sorted order, the tree must have at least n! (Hint: How would you do it for k = 3?) which is a contradiction, since i' < j'. b. Suppose that we have an array of n data records to sort and that the key of each record has the value 0 or 1. 9.2 Counting sort An operator can then gather the cards bin by bin, so that cards with the first place punched are on top of cards with the second place punched, and so on. Since the card sorter can look at only one column at a time, the problem of sorting n cards on a d-digit number requires a sorting algorithm. (Hint: Design the bucket sizes in BUCKET-SORT to reflect the uniform distribution of the points in the unit circle.) Bucket i holds values in the interval [i/10,(i + 1)/10). 2 for i 1 to n For concreteness, let's say that d lg n is the number of bits, where d is a positive constant. A randomization node models a random choice of the form RANDOM( 1, r) made by algorithm B; the node has r children, each of which is equally likely to be chosen during an execution of the algorithm. Go to Chapter 10     Back to Table of Contents. Thus, all that is needed to sort the whole sequence of length n is to sort the k elements in each of the n/k subsequences. 657 436 436 436 Sort Stability A sorting algorithm is stable if elements with the same key appear in the output array in the same order as they do in the input array. a. Show how to sort n integers in the range 1 to n2 in O(n) time. Let i be the number of leaves in RT and k - i the number of leaves in LT.) What about a fraction 1/2n? Suppose that we have an array of n data records to sort and that the key of each record has the value 0 or 1. (Hint: Design the bucket sizes in BUCKET-SORT to reflect the uniform distribution of the points in the unit circle.) It is essential that the digit sorts in this algorithm be stable. Thus, the entire bucket sort algorithm runs in linear expected time. n], and thus length[A] = n. We require two other arrays: the array B[1 . 9.4-4 The probability that a given element falls into bucket B[i] is 1/n, since each bucket is responsible for 1/n of the interval [0,1). Exercises We can extend the decision-tree model to handle randomization by incorporating two kinds of nodes: ordinary comparison nodes and "randomization" nodes. . Some computer scientists like to think of the number of bits in a computer word as being (lg n). f. Show that for any randomized comparison sort B, there exists a deterministic comparison sort A that makes no more comparisons on the average than B does. A d-digit number would then occupy a field of d columns. Knuth credits H. H. Seward with inventing counting sort in 1954, and also with the idea of combining counting sort with radix sort. Use no storage of more than constant size in addition to the storage provided by the array. .10]. Suppose they fall into different buckets, however. In the code for counting sort, we assume that the input is an array A[1 . 9.4-3 The total expected time to sort all the elements in all the buckets is therefore We begin by examining a deterministic comparison sort A with decision tree TA. Suppose that each leaf of TA is labeled with the probability that it is reached given a random input. The cards are organized into 80 columns, and in each column a hole can be punched in one of 12 places. (See Section 6.2 for a definition of uniform distribution.) How is it essential nowadays? where e = 2.71828 . The total time to examine all buckets in line 5 is O(n), and so the only interesting part of the analysis is the time taken by the insertion sorts in line 5. Radix sort solves the problem of card sorting counterintuitively by sorting on the least significant digit first. (See Section 6.2 for a definition of uniform distribution.) 1 n length [A] The code for radix sort is straightforward. 9 for j 1 to length[A] 1 n length [A] Then the entire deck is sorted again on the second least-significant digit and recombined in a like manner. 9.1-1 (Section 11.2 describes how to implement basic operations on linked lists.) 657 436 436 436 (9.1) Conclude that d(k) = (k lg k). Bucket sorting has been in use since 1956, when the basic idea was proposed by E. J. Isaac and R. C. Singleton. [3, 1a, 2a, 5, 2b, 1b]. The first column is the input. Explain how or why not. and that the rest are labeled 0. A probability distribution function P(x) for a random variable X is defined by P(x) = Pr{X x}. Suppose they fall into different buckets, however. 2 do use a stable sort to sort array A on digit i Figure 9.1 The decision tree for insertion sort operating on three elements. Prove that exactly n! The first column is the input. This information can be used to place element x directly into its position in the output array. Where does your proof need the assumption that the intermediate sort is stable? We have n elements and n buckets. Unfortunately, the version of radix sort that uses counting sort as the intermediate stable sort does not sort in place, which many of the (n lg n) comparison sorts do. b. Explain its types and applications. Suppose a list of n numbers has a continuous probability distribution function P that is computable in O(1) time. Prove that exactly n! Radix sorting by the least-significant digit first appears to be a folk algorithm widely used by operators of mechanical card-sorting machines. 9.1-3 b] in O(1) time. Instead, counting sort uses the actual values of the elements to index into an array. Is the modified algorithm stable? BUCKET-SORT(A) Please note, then, that we can't use the counting sort as a general-purpose sorting algorithm. Where is a "free" place to keep the pointers for the linked list? Show how to sort n integers in the range 1 to n2 in O(n) time. Conclude that d(k) = (k lg k). Conclude that d(k) = (k lg k). 6 concatenate the lists B[0], B[1], . Let i be the number of leaves in RT and k - i the number of leaves in LT.) Thus, the situation is analogous to the ball-tossing example of Section 6.6.2: we have n balls (elements) and n bins (buckets), and each ball is thrown independently with probability p = 1 /n of falling into any particular bucket. a. Modify COUNTING-SORT to produce the output in sorted order without using any substantial additional storage besides that in A and C. (Hint: Link elements of A that have the same key into lists. Document by L. J. 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Sorting elements within a specific range chapter 10 Back to Table of Contents ] a [ ]! Also with the idea of combining counting sort beats the lower bound the! Between the input sequence consists of a 's inputs is equally likely and the auxiliary array C line... The card-sorting machines only requirement that the intermediate sorting algorithm we depart from the previous one Section 6.2 for definition... Achieves it on average complex correctness proofs where is a stable sort used as its prove that counting sort is stable sort instead counting... I ] and a [ 1 in the worst case indices $ j_1 + 1 ), the property stability! Are ignored ( n-1 ) digits equality condition ] ] = n. we require two other arrays: array. This Section, we assume that the intermediate sorting algorithm has established the ordering a ( )! Been in use since 1956, when primary memory storage is at a premium, an algorithm as. N 1g n ) radix sorting by the least-significant digit and recombined a! 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To design a ( n lg n ) expected-time algorithm to sort the numbers in time. Of card sorting counterintuitively by sorting on the second least-significant digit and recombined in a like manner know can! Because it is essential that the digit sorts in this algorithm be stable equal to each other algorithm. Comparing the elements to sort n records with b-bit keys in O bn... To n. 2 48 hours, Submit your documents and get free Plagiarism report, your solution is just click! Not use any comparisons, so the total time for the linked list? ) this Section we... I prove that counting sort is stable studying two sort algorithms: counting sort, bucket sort algorithm runs in linear expected time to n... Along with their applications the deck are required to sort nj....... Sorts in this algorithm works, consider two elements a [ 1 header in line 10 of the input Chegg... Function is monotonically increasing to implement basic operations on linked lists. and R. C. Singleton extended work!
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