我最近复习了一些基础知识,发现对链表进行合并排序是一个很好的挑战。如果你有一个很好的实现,那么在这里展示它。
发布于 2011-11-23 14:46:38
不知道为什么它会是一个巨大的挑战,因为它在这里陈述,这是一个简单的Java实现,没有任何“聪明的技巧”。
//The main function
public static Node merge_sort(Node head)
{
if(head == null || head.next == null)
return head;
Node middle = getMiddle(head); //get the middle of the list
Node left_head = head;
Node right_head = middle.next;
middle.next = null; //split the list into two halfs
return merge(merge_sort(left_head), merge_sort(right_head)); //recurse on that
}
//Merge subroutine to merge two sorted lists
public static Node merge(Node a, Node b)
{
Node dummyHead = new Node();
for(Node current = dummyHead; a != null && b != null; current = current.next;)
{
if(a.data <= b.data)
{
current.next = a;
a = a.next;
}
else
{
current.next = b;
b = b.next;
}
}
dummyHead.next = (a == null) ? b : a;
return dummyHead.next;
}
//Finding the middle element of the list for splitting
public static Node getMiddle(Node head)
{
if(head == null)
return head;
Node slow = head, fast = head;
while(fast.next != null && fast.next.next != null)
{
slow = slow.next;
fast = fast.next.next;
}
return slow;
}发布于 2010-06-13 22:29:30
更简单/更清晰的实现可能是递归实现,它的NLog(N)执行时间更清晰。
typedef struct _aList {
struct _aList* next;
struct _aList* prev; // Optional.
// some data
} aList;
aList* merge_sort_list_recursive(aList *list,int (*compare)(aList *one,aList *two))
{
// Trivial case.
if (!list || !list->next)
return list;
aList *right = list,
*temp = list,
*last = list,
*result = 0,
*next = 0,
*tail = 0;
// Find halfway through the list (by running two pointers, one at twice the speed of the other).
while (temp && temp->next)
{
last = right;
right = right->next;
temp = temp->next->next;
}
// Break the list in two. (prev pointers are broken here, but we fix later)
last->next = 0;
// Recurse on the two smaller lists:
list = merge_sort_list_recursive(list, compare);
right = merge_sort_list_recursive(right, compare);
// Merge:
while (list || right)
{
// Take from empty lists, or compare:
if (!right) {
next = list;
list = list->next;
} else if (!list) {
next = right;
right = right->next;
} else if (compare(list, right) < 0) {
next = list;
list = list->next;
} else {
next = right;
right = right->next;
}
if (!result) {
result=next;
} else {
tail->next=next;
}
next->prev = tail; // Optional.
tail = next;
}
return result;
}注意:这对递归有Log(N)存储要求。性能应该与我发布的其他策略大致相当。通过运行合并循环while (list && right),并简单地附加剩余的列表(因为我们并不真正关心列表的结尾;知道它们被合并就足够了),这里有一个潜在的优化。
发布于 2010-06-13 21:53:46
大量基于来自:http://www.chiark.greenend.org.uk/~sgtatham/algorithms/listsort.html的优秀代码
稍微修剪一下,整理一下:
typedef struct _aList {
struct _aList* next;
struct _aList* prev; // Optional.
// some data
} aList;
aList *merge_sort_list(aList *list,int (*compare)(aList *one,aList *two))
{
int listSize=1,numMerges,leftSize,rightSize;
aList *tail,*left,*right,*next;
if (!list || !list->next) return list; // Trivial case
do { // For each power of two<=list length
numMerges=0,left=list;tail=list=0; // Start at the start
while (left) { // Do this list_len/listSize times:
numMerges++,right=left,leftSize=0,rightSize=listSize;
// Cut list into two halves (but don't overrun)
while (right && leftSize<listSize) leftSize++,right=right->next;
// Run through the lists appending onto what we have so far.
while (leftSize>0 || (rightSize>0 && right)) {
// Left empty, take right OR Right empty, take left, OR compare.
if (!leftSize) {next=right;right=right->next;rightSize--;}
else if (!rightSize || !right) {next=left;left=left->next;leftSize--;}
else if (compare(left,right)<0) {next=left;left=left->next;leftSize--;}
else {next=right;right=right->next;rightSize--;}
// Update pointers to keep track of where we are:
if (tail) tail->next=next; else list=next;
// Sort prev pointer
next->prev=tail; // Optional.
tail=next;
}
// Right is now AFTER the list we just sorted, so start the next sort there.
left=right;
}
// Terminate the list, double the list-sort size.
tail->next=0,listSize<<=1;
} while (numMerges>1); // If we only did one merge, then we just sorted the whole list.
return list;
}注意:这是O(NLog(N))保证的,并且使用O(1)资源(没有递归,没有堆栈,什么都没有)。
https://stackoverflow.com/questions/7685
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