怎么理解This line of code is searching for the index(position) of the substring "java" within the string "I love Java,java is very powerful!". It is case-sensitive, so it will only match the substring with lowercase 'j'. The result will depend on where the substring is found in the string. If it is found, the value of "index" will be the starting index of the first occurrence of the substring within the string. If the substring is not found, the value of "index" will be -1.

这段代码正在查找字符串"I love Java,java is very powerful!"中子字符串"java"的索引位置。它是大小写敏感的，因此只会匹配小写字母'j'的子字符串。结果将取决于子字符串在字符串中的位置。如果找到了子字符串，则"index"的值将是该子字符串在字符串中第一次出现的起始索引。如果未找到子字符串，则"index"的值将是-1。

相关问题

Binary search is a common search approach for a list of values. For binary search to work, the elements in the array must already be ordered. Assume that the array is in ascending order. The binary search first compares the key with the element in the middle of the array. Consider the following three cases: ■ If the key is less than the middle element, you need to continue to search for the key only in the first half of the array. ■ If the key is equal to the middle element, the search ends with a match. ■ If the key is greater than the middle element, you need to continue to search for the key only in the second half of the array. Implement the binary search using Language C. And write a program to test whether it can work or not.

Here is a sample implementation of binary search in C:

#include <stdio.h>

int binarySearch(int arr[], int left, int right, int key) {
    while (left <= right) {
        int mid = (left + right) / 2;
        if (arr[mid] == key) {
            return mid;
        }
        else if (arr[mid] < key) {
            left = mid + 1;
        }
        else {
            right = mid - 1;
        }
    }
    return -1;
}

int main() {
    int arr[] = { 2, 4, 6, 8, 10, 12, 14, 16, 18, 20 };
    int n = sizeof(arr) / sizeof(arr[0]);
    int key = 12;
    int index = binarySearch(arr, 0, n - 1, key);
    if (index == -1) {
        printf("Element not found\n");
    }
    else {
        printf("Element found at index %d\n", index);
    }
    return 0;
}

In this implementation, `binarySearch()` takes four arguments: the array to search `arr`, the left and right indices of the subarray to search `left` and `right`, and the key to search for `key`. It returns the index of the key in the array if it is found, or `-1` if it is not found.

The function works by repeatedly dividing the subarray in half using the middle index `mid`, comparing the key to the element at `arr[mid]`, and adjusting the left and right indices accordingly until the key is found or the subarray is exhausted.

In the `main()` function, we test the `binarySearch()` function by searching for the key `12` in the array `arr`. If the key is found, we print its index; otherwise, we print a message indicating that the element was not found.

Task 4.1 The following recursive algorithm performs a binary search in an ordered array. Test the algorithm by searching the value 105 from the array: A = [11, 23, 31, 47, 52, 68, 71, 89, 94, 105, 112, 126, 133, 148] Use recursion tree method to find out the complexity class of the algorithm, when the length of the array is the size of the input. The “r = ë(p + q)/2û” on line 7 means floor function. For example, ë11/2û = 5. Input: Array A[1,..,n], n >= 1, with elements in increasing order A[1] <= A[2] <= … <= A[n]. Numbers 1<=p<=q<=n. Number x that is searched in A[p,..,q]. Output: The index of x in the array or -1 if x is not present in A[p,..,q]. SEARCH(A,p,q,x) 1. if p==q 2. if A[p]==x 3. return p 4. else 5. return -1 6. else 7. r = ë(p + q)/2û 8. if x<=A[r] 9. return SEARCH(A,p,r,x) 10. else 11. return SEARCH(A,r+1,q,x)

你好！感谢你向我提出问题。我是 ChatGPT，一个基于人工智能的语言模型，我会尽我所能来回答你的问题。

关于你提出的问题，这是一道关于算法的问题，涉及到递归和二分查找算法的复杂度分析。我会尽我所能来解答这个问题，但是由于我并不是专业的数学家或者计算机科学家，我的回答可能会有一些不足之处，希望你能理解。

首先，这个算法是一个二分查找算法，它采用递归方式实现。对于一个有序数组，它首先检查数组的中间元素，然后根据比较结果将搜索范围缩小到左半部分或右半部分。然后，它递归地在所选范围内进行查找，直到找到目标元素或搜索范围为空为止。

为了分析这个算法的复杂度，我们可以使用递归树的方法来计算它的运行时间。递归树是一个树形结构，它描述了递归算法的运行方式。在二分查找算法中，递归树的深度是 log(n)，因为每次递归都将搜索范围减半。因此，我们需要在 log(n) 层中找到目标元素。

在每一层中，算法都需要执行一个常数时间的操作，即比较数组的中间元素和目标元素。因此，算法的总运行时间是 O(log(n))，其中 n 是数组的长度。这是因为算法在最坏情况下需要查找整个数组，而数组的长度是 n。

对于给定的数组 A = [11, 23, 31, 47, 52, 68, 71, 89, 94, 105, 112, 126, 133, 148]，如果我们要搜索值为 105 的元素，那么算法需要在第三次递归时找到它。因此，算法的复杂度类别是 O(log(n))。

最后，关于题目中的 floor 函数，它的作用是将一个实数向下取整。例如，floor(11/2) = 5。在算法中，它被用来计算数组的中间位置。

希望我的解答能对你有所帮助，如果你有其他问题，欢迎随时向我提问。