[LeetCode] Search for a Range [34]

题目

Given a sorted array of integers, find the starting and ending position of a given target value.

Your algorithm's runtime complexity must be in the order of O(log n).

If the target is not found in the array, return [-1, -1].

For example,
Given [5, 7, 7, 8, 8, 10] and target value 8,
return [3, 4].

原题链接(点我)

解题思路

查找一个数出现的范围,给一个排好序的数组和一个数,找出这个数在数组中出现的范围。
这个题直接使用一次遍历就可以得到结果,这样的时间复杂度为O(n)。但是对于有序数组我们一般可以使用二分查找可以得到更好的O(logn)的时间复杂度。我们可以使用二分查找找到这个数第一次出现的位置和这个数最后一次出现的位置,这样就可以得到它出现的区间。

代码实现
class Solution {
public:
    vector<int> searchRange(int A[], int n, int target) {
        vector<int> ret;
        if(A==NULL || n<=0) return ret;
        int first = getFirst(A, n, target);
        int last = getLast(A, n, target);
        ret.push_back(first);
        ret.push_back(last);
        return ret;
    }
    int getFirst(int A[], int n, int target){
        int begin = 0, end = n-1;
        int mid;
        while(begin<=end){
            int mid = (begin+end)/2;
            if(A[mid] == target){
                if(mid==0 || A[mid-1]<A[mid])
                    return mid;
                else
                    end = mid-1;
            }else if(A[mid] < target)
                begin = mid+1;
            else
                end = mid-1;
        }
        return -1;
    }
    int getLast(int A[], int n, int target){
        int begin = 0, end = n-1;
        int mid;
        while(begin<=end){
            int mid = (begin+end)/2;
            if(A[mid] == target){
                if(mid==n-1 || A[mid+1]>A[mid])
                    return mid;
                else
                    begin = mid+1;
            }else if(A[mid] < target)
                begin = mid+1;
            else
                end = mid-1;
        }
        return -1;
    }
};

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(转载文章请注明出处: http://blog.youkuaiyun.com/swagle/article/details/30466235 )

### LeetCode Problem 34: Find First and Last Position of Element in Sorted Array The task involves finding the starting and ending position of a given target value within an array of integers. If the target is not found in the array, [-1, -1] should be returned. For instance, consider an input where `nums` = [5,7,7,8,8,10], and `target` = 8. The expected output would be [3, 4]. Another example could involve `nums` = [5,7,7,8,8,10], but this time with `target` = 6, leading to an output of [-1, -1]. To solve this problem efficiently: A binary search approach can achieve logarithmic complexity by narrowing down potential positions for both the first and last occurrence of the target element[^1]: ```python def searchRange(nums, target): def findLeftIndex(nums, target): left, right = 0, len(nums) - 1 while left <= right: mid = (left + right) // 2 if nums[mid] < target: left = mid + 1 else: right = mid - 1 return left def findRightIndex(nums, target): left, right = 0, len(nums) - 1 while left <= right: mid = (left + right) // 2 if nums[mid] <= target: left = mid + 1 else: right = mid - 1 return right left_index = findLeftIndex(nums, target) right_index = findRightIndex(nums, target) # Check if the target exists in the list. if left_index <= right_index < len(nums) and nums[left_index] == target: return [left_index, right_index] return [-1, -1] ``` This code snippet defines two helper functions that perform modified versions of binary searches—one looking for the start index (`findLeftIndex`) and another for the end index (`findRightIndex`). After determining these indices, it checks whether they are valid before returning them as part of the result.
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