算法导论（第三版）练习 2.3-1 ~ 2.3-7

2.3-1

【31,41】,52,26,38,57,9,49
31,41,【26,52】,38,57,9,49
【26,31,41,52】,38,57,9,49
26,31,41,52,【38,57】,9,49
26,31,41,52,38,57,【9,49】
26,31,41,52,【9,38,49,57】
【9,26,31,38,41,49,52,57】

2.3-2

js代码：

                static merge2(arr, start, mid, end)     {
                    let left = arr.slice(start, mid); // arr[mid] is excluded
                    let right = arr.slice(mid, end);
                    
                    let i = 0, j = 0; // index of left and right
                    let k =  start; // index of arr
                    while(i < left.length && j < right.length) {
                        arr[k++] = left[i] < right[j] ? left[i++] : right[j++];                        
                    }
                    
                    if (i == left.length) {
                        left = right;
                        i = j;
                    } else {
                        i = i;
                    }

                    while (k < end) {
                        arr[k++] = left[i++];
                    }
                }

2.3-3

证明 T(n) = nlgn ↓
当 n = 2^1时，T(2) = 2 = 2 * lg2 成立，
假设当 n = 2^k 时，T(2^k) = 2^k * lg(2^k) = 2^k * k 成立，
当 n = 2^(k+1)时，T(2^(k+1)) = 2 * (2^k * k) + 2^(k+1) = 2^(k+1) * (k+1) 
因此 T(n) = nlgn 成立。

View Code

2.3-4

 js代码：

            class InsertSort {
                static sort(arr, start, end) {
                    if (end - start > 1) {                
                        InsertSort.sort(arr, start, end - 1);                    
                        let key = arr[end - 1];
                        let i = end - 2; // point to the number which 'key' prepare to compare
                        while (i >= start && arr[i] > key) {
                            arr[i + 1] = arr[i];
                            i--;
                        }
                        arr[i + 1] = key;
                    } else {
                        return;
                    }
                }
                
                static run(data) {
                    // convert a string to a numeric array
                    data = CommonUtil.handleData(data); 
                    
                    InsertSort.sort(data, 0, data.length);
                    console.log(data);
                }
            }

View Code

2.3-5

js代码：

                static find(x, arr, start, end) {
                    if (start > end) return { success: false};
                    let mid = Math.floor((start + end) / 2);
                    if (arr[mid] == x) {
                        return { success: true, index: mid};
                    } else if (arr[mid] < x) {
                        return BinarySearch.find(x, arr, mid + 1, end);
                    } else {
                        return BinarySearch.find(x, arr, start, mid - 1);
                    }
                }

最坏情况就是找不到，二分查找的递归式：

根据书上的递归树得到总代价为clgn + c，因此最坏情况运行时间是theta lgn

2.3-6

换一种数据结构也许可以，采用数组做不到（查找位置lgn插入时间n，总时间还是n^2）。

附加：二叉搜索树(平均情况nlgn，最坏n^2) VS. 插入排序（n^2），两万数据实测↓

重复排序100次：

2.3-7

js代码描述：

            class IntegerSum {
                static searchSum(arr, start, end, x) {
                    if (end - start <= 1) return false;
                    
                    let sum = arr[start] + arr[end - 1];
                    if (sum < x) {
                        return IntegerSum.searchSum(arr, start + 1, end, x);
                    } else if (sum > x) {
                        return IntegerSum.searchSum(arr, start, end - 1, x);
                    } else {
                        console.log(arr[start], arr[end - 1]);
                        return true;
                    }
                }
                
                static run(data) {
                    data = CommonUtil.handleData(data); // cn
                    MergeSort.sort(data, 0, data.length); // cnlgn
                    // let x = Number(prompt("please enter the value of x :"));
                    let x = Math.floor(Math.random() * 40);
                    console.log("data=" + data);
                    console.log("x=" + x);
                    
                    let end = -1;
                    while (data[++end] <= x); // cn
                    
                    let result;
                    let max = data[end - 1] + data[end - 2];
                    let min = data[0] + data[1];
                    if (max < x || min > x) { // deal with special situations 
                        result = false; 
                    }  else if (max == x || min == x) {
                        result = true;        
                    } else {
                        result = IntegerSum.searchSum(data, 0, end, x); // cn
                    }
                    console.log(result);
                }
            }