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private static void heapify(int[] a, int i, int j) { int ai = a[i]; // step 1 48 while (2*i+1 < j) { 49 int k = 2*i + 1; 50 if (k + 1 < j && a[k+1] > a[k]) { 51 ++k; // a[k] is the larger child 52 } 53 if (ai >= a[k]) { 54 break; // step 3 55 } 56 a[i] = a[k]; // step 4 57 i = k; // step 5 58 } 59 a[i] = ai; // step 7 60 } The sort() function first converts the array so that its underlying complete binary tree is transformed into a heap. This is done by applying the heapify() function to each nontrivial subtree. The nontrivial

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[A3(z) - T ~ Z - ~ A ~ ( Z - ' ) ] I - r:

Algorithm 14.10 The Radix Sort (Precondition: s = {s0 . . . sn 1} is a sequence of n integers or character strings with radix r and width w.) (Postcondition: The sequence s is sorted numerically or lexicographically.) 1. Repeat step 2 for d = 0 up to w 1. 2. Apply a stable sorting algorithm to the sequence s, sorting only on digit number d. A sorting algorithm is said to be stable if it preserves the relative order of elements with equal keys. For example, the insertion sort is stable, but the heap sort is not. EXAMPLE 14.12 Sorting ISBNs with the radix sort

1 [ I - 0.8z-~ 1 - (0.512)

46 47

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+ 0 . 6 4 ~ ~ ' 0.512z--' + 0 . 5 1 2 ~ - ~ (- 0.82 + 0.64z2 - 0.512z3)] 1

Figure 14.5 shows a sequence of 12 ISBNs and the first four iterations of the radix sort applied to it.

= 1 - 0.64Olz-'

subtrees (i.e., those having more than one element) are the subtrees that are rooted above the leaf level. In the array, the leaves are stored at positions a[n/2] through a[n]. So the first for loop in the sort() function applies the heapify() function to elements a[n/2-1] back through a[0] (which is the root of the underlying tree). The result is an array whose corresponding tree has the heap property, illustrated in Figure 14.3.

I A,(z) = [Az(z)- r 2 ~ - 2 ~ ~ ( ~ - ' ) 1

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Note how the stability is needed to conserve the work done by previous iterations. For example, after the first iteration, 8838650527 precedes 0830636528 because 7 < 8. Both of these keys have the same value 2 in their second least significant digit (digit number d = 1). So on the second iteration, which sorts only on digit number 1, these two keys evaluate as being equal. But they should retain their previous relative order because 27 < 28. Stability guarantees that they do. The columns that have been processed are shaded. So after the third iteration, the right-most 3-digit subsequences are sorted: 109 < 13X < 373 < 453. (Note that X stands for the value 10. So 13X numerically means 130 + 10 = 140.)

1 - (0.3 123)2

Now the main (second) for loop progresses through n-1 iterations. Each iteration does two things: it swaps the root element with element a[i], and then it applies the heapify() function to the subtree of elements a[0..i). That subtree consists of the part of the array that is still unsorted. Before the swap() executes on each iteration, the subarray a[0..i] has the heap property, so a[i] is the largest element in that subarray. That means that the swap() puts element a[i] in its correct position. The first seven iterations of the main for loop have the effect shown by the seven pictures in Figure 14.4 on page 268. The array (and its corresponding imaginary binary tree) is partitioned into two parts: The first part is the subarray a[0..i) that has the heap property, and the second part is the remaining a[i..n) whose elements are in their correct positions. The second part is shaded in each of the seven pictures in Figure 14.4 on page 268. Each iteration of the main for loop decrements the size of the first part and increments the size of the second part. So when the loop has finished, the first part is empty and the second (sorted) part constitutes the entire array. This analysis verifies the following theorem.

[I - 0.6401~-' 0.3123~-' - 0 . 3 1 2 3 ~ - ~ ( 1 0.64012 -

CHAP. 14]

+ 0.3123z2)]

= 1 - 0.4878~-'

This method assumes that the constants RADIX has WIDTH have been defined. For example, for arrays of ints:

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