Void merge(Element* initList, Element* mergeList, const int l, const int m, const int n) { for (int i1 =l,iResult = l, i2 = m+1; i1<=m && i2<=n; iResult++){

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Presentation transcript:

void merge(Element* initList, Element* mergeList, const int l, const int m, const int n) { for (int i1 =l,iResult = l, i2 = m+1; i1<=m && i2<=n; iResult++){ if (initList[i1].getKey() <= initList[i2].getKey()) { mergeList[iResult] = initList[i1]; i1++; } else { mergeList[iResult] = initList[i2]; i2++; } if (i1 > m) for (int t = i2; t <= n; t++) mergeList[iResult + t - i2] = initList[t]; else for (int t = i1; t <= m; t++) mergeList[iResult + t - i1] = initList[t]; }

Iterative Merge Sort Treat the input as n sorted lists, each of length 1. Lists are merged by pairs to obtain n/2 lists, each of size 2 (if n is odd, the one list is of length 1). The n/2 lists are then merged by pairs, and so on until we are left with only one list.

Merge Tree

Iterative Merge Sort void MergeSort(Element* list, const int n) // Sort list list into non-decreasing order of the keys list[1].key, …,list[n].key. { Element* tempList = new Element[n+1]; // l is the length of the sublist currently being merged. for (int l = 1; l < n; l *= 2) { MergePass(list, tempList, n, l); l *= 2; MergePass(tempList, list, n, l); //interchange role of list and tempList } delete[ ] tempList; }

Merge Pass void MergePass(Element* initList, Elemen* resultList, const int n, const int l) // One pass of merge sort. Adjacent pairs of sublists of length l are merged // from list initList to list resultList. n is the number of records in initList { for (int i = 1; i <= n – 2*l + 1; // Are enough elements remaining to form two sublists of length l? i += 2*l) merge(initList, resultList, i, i + l - 1, i + 2*l – 1); // merge remaining list of length < 2 * l if ((i + l – 1) < n) merge(initList, resultList, i, i+l–1, n); else for (int t = i; t <= n; t++) resultList[t] = initList[t]; }

Analysis of MergeSort Total of passes are made over the data. Each pass of merge sort takes O(n) time. The total of computing time is O(n log n)