1  BST迭代器

注意点:1. 实际就是中序遍历的非递归写法,迭代器就是要用Stack存储数据,不过把不同的模块功能进行了分割,而不是一次完成中序遍历;

    2. 可以把添加到Stack单独抽取成一个函数,面向对象,更容易理解。

http://www.lintcode.com/en/problem/binary-search-tree-iterator/#

 1  public class BSTIterator {
 2     //@param root: The root of binary tree.
 3     TreeNode next = null;
 4     Stack<TreeNode> stack = new Stack<TreeNode>();
 5     public BSTIterator(TreeNode root) {
 6         // write your code here
 7         next = root;
 8     }
 9 
10     //@return: True if there has next node, or false
11     public boolean hasNext() {
12         // write your code here
13         while(next != null) {
14             stack.push(next);
15             next = next.left;
16         }
17         if(stack.isEmpty()) return false;
18         return true;
19     }
20     
21     //@return: return next node
22     public TreeNode next() {
23         // write your code here
24         if(!hasNext()) return null;
25         TreeNode cur = stack.pop();
26         if(cur.right == null) next = null;
27         else next = cur.right;
28         return cur;
29     }
30 }
View Code

 

2 二叉查找树中搜索

注意点:见代码

    不一定要完全遍历二叉树,可以在遍历前判断下来减少遍历的量。

    if(root.val > k1)  helper(root.left, result, k1, k2);

http://www.lintcode.com/zh-cn/problem/search-range-in-binary-search-tree/

 1 //可以定义一个 ArrayList<Integer> result的成员变量,这样helper中就不需要resul作为参数一直传递添加了。
 2   public ArrayList<Integer> searchRange(TreeNode root, int k1, int k2) {
 3      ArrayList<Integer> result = new ArrayList<Integer> ();
 4      helper(root, result, k1, k2);
 5      return result;
 6  }
 7  private void helper(TreeNode root, ArrayList<Integer>  result, int k1, int k2) {
 8      if(root == null) return;
 9      helper(root.left, result, k1, k2);
10      if(root.val >= k1 && root.val <= k2) result.add(root.val);
11      helper(root.right, result, k1, k2);
12      return;
13  }
View Code

 

3 二叉树中插入结点

http://www.lintcode.com/en/problem/insert-node-in-a-binary-search-tree/

注意点:非递归的插入方式

 1  public TreeNode insertNode(TreeNode root, TreeNode node) {
 2         // write your code here
 3         if(root == null) {
 4             root = node;
 5             return root;
 6         }
 7         if(root.val <= node.val) {
 8             root.right = insertNode(root.right, node);
 9             
10         } else {
11             root.left = insertNode(root.left, node);
12         }
13         return root;
14     }
15 //非递归
16  public TreeNode insertNode(TreeNode root, TreeNode node) {
17         // write your code here
18         if(root == null) {
19             root = node;
20             return root;
21         }
22         TreeNode last = null, temp = root;
23         while(temp != null) {
24             last = temp;
25             if(temp.val <= node.val) temp = temp.right;
26             else temp = temp.left;
27         }
28         if(last != null) { //可以不判断,last不可能为null
29             if(last.val <= node.val) last.right = node;
30             else last.left = node;
31         }
32         return root;
33     }
34     
View Code

4  二叉树删除结点

http://www.lintcode.com/en/problem/remove-node-in-binary-search-tree/

注意点:见代码

    结点的传递是地址传递,所以将待改变结点的引用传入函数,函数操作后,整个树是会发生变化的。

    待删结点有两个子树的删除方式:

  

 1 public TreeNode removeNode(TreeNode root, int value) {
 2         TreeNode dummy = new TreeNode(0); //dummy的值随便取,反正不输出,为了仅仅是给root设个头
 3         dummy.left = root; 
 4         
 5         TreeNode parent = findNode(dummy, root, value);
 6         TreeNode node; //待删结点
 7         if (parent.left != null && parent.left.val == value) {
 8             node = parent.left;
 9         } else if (parent.right != null && parent.right.val == value) {
10             node = parent.right;
11         } else {
12             return dummy.left ;  //待删结点不存在
13         }
14         
15         deleteNode(parent, node);
16         
17         return dummy.left ;
18     }
19     
20     private TreeNode findNode(TreeNode parent, TreeNode node, int value) {  //返回待删结点的父节点,待删的不存在也返回父节点
21         if (node == null) {
22             return parent;
23         }
24         
25         if (node.val == value) {
26             return parent;
27         }
28         if (value < node.val) {
29             return findNode(node, node.left, value);
30         } else {
31             return findNode(node, node.right, value);
32         }
33     }
34     
35     private void deleteNode(TreeNode parent, TreeNode node) {
36         if (node.right == null) {
37             if (parent.left == node) {
38                 parent.left = node.left;
39             } else {
40                 parent.right = node.left;
41             }
42         } else {
43             TreeNode temp = node.right;
44             TreeNode father = node;
45             
46             while (temp.left != null) {
47                 father = temp;
48                 temp = temp.left;
49             }
50             
51             if (father.left == temp) {
52                 father.left = temp.right;
53             } else {
54                 father.right = temp.right;
55             }
56             
57             if (parent.left == node) {
58                 parent.left = temp;
59             } else {
60                 parent.right = temp;
61             }
62             
63             temp.left = node.left;
64             temp.right = node.right;
65         }
66     }
View Code

 DP--------------------------------------------------------------------------------------------------------------------------------------------------------------------

满足下面三个条件之一:
● 求最大值最小值
● 判断是否可行
● 统计方案个数
则 极有可能 是使用动态规划求解

序列型dp 递推表达式f[] 里代表着含有0个~length个字符,所以数组的长度定义为length+1;
区间型dp 递推表达式f[] 里代表着坐标,所以数组的长度定义为length;

 

1  数字三角形

http://www.lintcode.com/zh-cn/problem/triangle/

疑问: 用HashMap怎么存?编译不通过?????

注意点:top- down 、down - top、 记忆化搜索

    初始化三角形的顶点和两个侧边

错误点:

 

 1 //搜索记忆,查找过的结点不需要再查一次,所以复杂度为O(n * n)
 2 int[][] triangle = null;
 3 int[][] sumMin = null;
 4 int n;
 5 public int minimumTotal(int[][] triangle) {
 6     if(triangle == null || triangle.length == 0 || triangle[0].length == 0) return 0;
 7     this.n = triangle.length;
 8     this.triangle = triangle;
 9     this.sumMin = new int[n][n];
10     for(int i = 0; i< n; i++) {
11         for(int j = 0; j < n ; j++) sumMin[i][j] = Math.MAX_VALUE;
12     }
13     
14     return helper(0, 0);
15 }
16 private  int helper(int x, int y) {
17     if(x >= n) return 0;
18     if(sumMin[x][y] != Math.MAX_VALUE) return sumMin[x][y];
19     sumMin[x][y] = Math.min(helper(x+1, y),helper(x+1,y+1)) + triangle[x][y];
20     return  sumMin[x][y];
21 }
22 // 同上,用哈希表存查过的结点
23 int[][] triangle = null;
24 HashMap<int[], Integer> sumMin = new HashMap<int[], Integer>();
25 int n;
26 public int minimumTotal(int[][] triangle) {
27     if(triangle == null || triangle.length == 0 || triangle[0].length == 0) return 0;
28     this.n = triangle.length;
29     this.triangle = triangle;
30     for(int i = 0; i< n; i++) {
31         for(int j = 0; j < n ; j++) sumMin[i][j] = Math.MAX_VALUE;
32     }
33     
34     return helper(0, 0);
35 }
36 private  int helper(int x, int y) {
37     if(x >= n) return 0;
38     if(sumMin.containsKey({x,y})) return sumMin.get({x,y});
39     int value = Math.min(helper(x+1, y),helper(x+1,y+1)) + triangle[x][y];
40     sumMin.put({x,y}, value);
41     return  value;
42 }
43 //top - down
44 public int minimumTotal(int[][] triangle) {
45     if(triangle == null || triangle.length == 0 || triangle[0].length == 0) return 0;
46     int row = triangle.length;
47     for(int i =1; i < row; i++) {
48         triangle[i][0] +=  triangle[i-1][0];
49         triangle[i][i] += triangle[i-1][i-1];
50     }
51     for(int i = 2; i < row; i++) {
52         for(int j =1; j < i; j++) {
53             triangle[i][j] += Math.min(triangle[i-1][j],triangle[i-1][j-1]);
54         }
55     }
56     for(int i = 1; i < row; i++) {
57         triangle[row-1][0] = Math.min(triangle[row-1][i],triangle[row-1][0]);
58     }
59     return triangle[row-1][0];
60 }
61 //down - top
62 public int minimumTotal(int[][] triangle) {
63     if(triangle == null || triangle.length == 0 || triangle[0].length == 0) return 0;
64     int row = triangle.length;
65     for(int i= row -2; i >=0; i--) {
66         for(int j=0; j<= i; j++)
67         triangle[i][j] += Math.min(triangle[i+1][j], triangle[i+1][j+1]);
68     }
69     return triangle[0][0];
70 }
View Code

 

2 爬梯子

http://www.lintcode.com/zh-cn/problem/climbing-stairs/

注意点:类似斐波那契别超时~

 1 public int climbStairs(int n) { 
 2      if(n == 0) return 1;
 3     a = 1;
 4     b = 1;
 5     for(int i = 2; i <= n; i++) {
 6         int c = a+ b;
 7         c= b;
 8         a = b;
 9     }
10     return c;
11  }
12 //---------------------
13  public int climbStairs(int n) { 
14     int[] f = new int[n+1];
15     if(n == 0) return 1;
16     f[0] = 1;
17     f[1] = 1;
18     for(int i = 2; i <= n; i++) {
19         f[i] = f[i - 1] + f[i - 2];
20     }
21     return f[n];
22  }
更新版本1
 1 // 递归调用会超时,因为有重复计算的过程
 2    public int climbStairs(int n) {
 3        if(n == 0) return 1;
 4        if(n == 1) return 1;
 5        return climbStairs(n-2)+climbStairs(n-1);
 6    }
 7  //  加入记忆化搜索,还超时
 8  int[] result = null;
 9    public int climbStairs(int n) {
10        result = new int[n];
11        Arrays.fill(result, -1);
12        if(n == 0) return 1;
13        if(n == 1) return 1;
14        result[0] = 1,   result[1] = 1;
15        return helper(n);
16    }
17    private int helper(n) {
18        if(result[n] != -1) return result[n];
19        return helper(n-1) + helper(n-2);
20    }
21    //
22     public int climbStairs(int n) {
23          if(n <=1) return 1;
24          int last = 1, last_last = 1;
25          int now = 0;
26          for(int i=1 ; i< n;i++) {
27              now = last + last_last;
28              last_last = last;
29              last = now;
30          }
31          return now;
32      }
View Code

3 跳跃游戏

http://www.lintcode.com/zh-cn/problem/jump-game/

注意点:O(N * N)的时间复杂度

错误点:

 1  //  me
 2    public boolean canJump(int[] A) {
 3         // wirte your code here
 4         if(A == null || A.length == 0) return false;
 5         int n = A.length;
 6         int pos =0;
 7         while(pos <= n -1) {
 8             if(A[pos] >= n - 1 - pos) return true;
 9             else {
10                 int temp = pos + A[pos];
11                 while(A[temp] == 0) {
12                     temp--;
13                     if(temp <= pos) return false;
14                 }
15                 pos = temp;
16             } 
17         }
18         return false;        
19     }
20 // greedy
21 public boolean canJump(int[] A) {
22     if(A == null || A.length == 0) return false;    
23     int farthest = A[0];
24     for(int i = 1; i< A.length; i++) {
25         if(farthest >= i && farthest < i+ A[i]) {
26             farthest = i + A[i];
27         }
28     }
29     return farthest>= A.length - 1;
30 }
31 //dp
32     public boolean canJump(int[] A) {
33     if(A == null || A.length == 0) return false;
34     boolean[] can = new boolean[A.length];
35     can[0] = true;
36     for(int i = 1; i < A.length; i++) {
37         for(int j = 0; j < i; j++) {
38             if(can[j] && A[j] + j >= i) {
39                 can[i] = true;
40                 break;
41             }
42         }
43     }
44     return can[A.length - 1];
45 }
View Code

4  跳跃游戏二

http://www.lintcode.com/zh-cn/problem/jump-game-ii/

注意点:

错误点:结果数组没有初始化,数组间的关系没搞清楚

 1 public int jump(int[] A) {
 2         // state
 3         int[] steps = new int[A.length];
 4 
 5         // initialize
 6         steps[0] = 0;
 7         for (int i = 1; i < A.length; i++) {
 8             steps[i] = Integer.MAX_VALUE;
 9         }
10 
11         // function
12         for (int i = 1; i < A.length; i++) {
13             for (int j = 0; j < i; j++) {
14                 if (steps[j] != Integer.MAX_VALUE && j + A[j] >= i) {
15                     //steps[i] = Math.min(steps[i], steps[j] + 1);
16                     steps[i] = steps[j] + 1;
17                     break; //贪心
18                 }
19             }
20         }
21         
22         // answer
23         return steps[A.length - 1];
24     }
View Code

5  two Sum

http://www.lintcode.com/en/problem/two-sum/

注意点: map里存需要的值和它的角标;

 1 //dp
 2   public int[] twoSum(int[] numbers, int target) {
 3     // write your code here
 4     HashMap<Integer, Integer> map = new HashMap<Integer, Integer>();
 5     for(int i = 0 ; i< numbers.length; i++) {
 6         if(map.get(numbers[i]) != null) {
 7             int[] result = {map.get(numbers[i]) + 1, i+1};
 8             return result;
 9         }
10         // if在前,put在后,一定要这样,先看有没有再放。
11         map.put(target - numbers[i], i);
12     }
13     int[] result = {};
14     return result;
15  }
16 //---------------------------
17 public int[] twoSum(int[] numbers, int target) {
18     // write your code here
19     if(numbers == null || numbers.length <= 1) return null;
20     for(int i = 0; i< numbers.length - 1; i++) {
21         for(int j = i+1; j< numbers.length; j++) {
22             if(numbers[i] == target - numbers[j]) return new int[]{i + 1, j + 1};
23         }
24     }
25     return null;
26  }
View Code

 6 k sum   不会

http://www.lintcode.com/zh-cn/problem/k-sum/

 7 最长上升连续子序列

http://www.lintcode.com/zh-cn/problem/longest-increasing-continuous-subsequence/

注意点:

 1 public int longestIncreasingContinuousSubsequence(int[] A) {
 2     if(A == null || A.length == 0) return 0;
 3     int[] result = new int[A.length];
 4     Arrays.fill(result, 1);
 5     int max = 1;
 6     for(int i = 1; i< A.length; i++) {
 7         if(result[i -1] == 1) {
 8             result[i] =2;
 9             if(max < result[i]) max = result[i];
10             continue;
11         }
12         if(A[i-2] < A[i -1] && A[i-1] < A[i] ||
13         A[i-2] > A[i-1] && A[i-1] > A[i])
14         result[i] =  result[i- 1]+1;
15         else result[i] = 2;
16         if(max < result[i]) max = result[i];
17     }
18     return max;
19 }
20 //------------------------------------------------------------
21 public int longestIncreasingContinuousSubsequence(int[] A) {
22     if(A == null || A.length == 0) return 0;
23     int max = 1;
24     int length =1;
25     for(int i = 1; i < A.length; i++) {
26         if(A[i] > A[i-1]) length++;
27         else length=1;
28         max= Math.max(length, max);
29     }
30     for(int i = A.length -2; i >=0; i--) {
31         if(A[i+1] < A[i]) length++;
32         else length=1;
33         max= Math.max(length, max);
34     }
35     return max;
36 }
View Code

 8 最长连续序列

http://www.lintcode.com/zh-cn/problem/longest-consecutive-sequence/

注意点: 求数组中连续序列个数的两种方式: 

       先排序,在求最长的递增序列长度;

       把元素放到set里,之后遍历数组,查找是否包含连续序列,见代码。

 1 public int longestConsecutive(int[] num) {
 2      if(num == null || num.length == 0) return 0;
 3      int[] sortArray = bucketSort(num);
 4      int[] f= new int[sortArray.length];
 5      f[0] = 1;
 6      int maxLen = 1;
 7      for(int i = 1; i < sortArray.length; i++) {
 8          f[i] = 1;
 9          if(sortArray[i] == sortArray[i -1] + 1) {
10              f[i] = f[i - 1] + 1;
11          } else if(sortArray[i] == sortArray[i -1]) f[i] = f[i - 1];
12          if(maxLen < f[i]) maxLen = f[i];
13      }
14      return maxLen;
15  }
16  private int[] bucketSort(int[] num) {
17      if(num == null || num.length == 0) return null;
18      int max = 0, min = 0;
19      for(int i : num) {
20          if(max <= i) max = i;
21          if(min >= i) min = i;
22      }
23      long[] bucket = new long[max - min + 1];
24      for(int i : num) {
25          //如果min= 3, 4应该放在1的位置
26          bucket[i - min]++;
27      }
28      int[] result = new int[num.length];
29      int i = 0;
30      for(int j = 0; j < bucket.length; j++) {
31         if(bucket[j] == 0) continue;
32         while(bucket[j] != 0) {
33             result[i] = j + min;
34             bucket[j] -= 1;
35             i++;
36         }        
37      }
38      return result;
39  }
先进行桶排序,有NegativeArraySizeException
 1  public int longestConsecutive(int[] num) {
 2      if(num == null || num.length == 0) return 0;
 3      Set<Integer> set = new HashSet<Integer>();
 4      for(int i : num) set.add(i);
 5      int max = 0;
 6      for(int i = 0; i< num.length; i++) {
 7          int down = num[i];
 8          while(set.contains(down)) {
 9              set.remove(down);
10              down--;
11          }
12          int up = num[i] + 1;
13          while(set.contains(up)) {
14              set.remove(up);
15              up++;
16          }
17          max = Math.max(max, up-down - 1);
18      }
19      return max;
20  }
View Code
 1 public int longestConsecutive(int[] num) {
 2     if(num == null || num.length == 0) return 0;
 3     int max = 1;
 4     Arrays.sort(num);
 5     HashMap<Integer,Integer> map = new HashMap<Integer, Integer>();
 6     for(int i = 0; i < num.length; i++) {
 7         if(map.get(num[i]) != null) {
 8             map.put(num[i] + 1, map.get(num[i]) + 1);
 9         } else     map.put(num[i] + 1, 1);
10         max = Math.max(max, map.get(num[i] + 1));
11     }
12     return max;
13 }
14 //用set存放,while循环找顺序序列,而不需要提前排序
15  public int longestConsecutive(int[] num) {
16     if(num == null || num.length == 0) return 0;
17     HashSet<Integer> set = new HashSet<Integer>();
18     for(int i = 0; i < num.length; i++) {
19         set.add(num[i]);
20     }
21     int max = 1;
22     for(int i=0;i< num.length; i++) {
23         int down = num[i] - 1;
24         while(set.contains(down)) {
25             set.remove(down);
26             down--;
27         }
28         int up = num[i] + 1;
29         while(set.contains(up)) {
30             set.remove(up);
31             up++;
32         }
33         max = Math.max(max, up - down -1);
34     }
35     return max;
36 }
View Code

 9 最大子数组  部分答案看不懂,还是不懂~~~

http://www.lintcode.com/zh-cn/problem/maximum-subarray/

注意点:

 1 public int maxSubArray(int[] nums) {
 2     //错误点: 没有考虑到 4,-1,2,1 这种情况,应该是6,目前结果时4.
 3     if(nums == null || nums.length == 0) return 0;
 4     int[] f = new int[nums.length];
 5     int max = f[0] =  nums[0];
 6     for(int i = 1; i < nums.length; i++) {
 7         if(nums[i] >= 0) {
 8             if(f[i - 1] >=0) f[i] = f[i-1] + nums[i];
 9             else f[i] = nums[i];
10         } else {
11             if(f[i - 1] < nums[i]) f[i] = nums[i];
12             else f[i] = nums[i];
13             
14         }
15         max = Math.max(max, f[i]);
16     }
17     return max;
18 }
19 public int maxSubArray(int[] nums) {
20     if(nums == null || nums.length == 0) return 0;
21     int max = nums[0], sum = 0;
22     for(int i = 0; i < nums.length; i++) {
23         sum +=nums[i];
24         max = Math.max(sum, max);
25         sum = Math.max(sum, 0);
26     }
27     return max;
28 }
1
 1  public int maxSubArray(int[] nums) {
 2     int max = Integer.MIN_VALUE, sum = 0;
 3     if(nums == null || nums.length  ==0) return 0;
 4     for(int i =0; i < nums.length; i++) {
 5         sum += nums[i];
 6         max = Math.max(sum, max); //用max记录每次sum后现阶段遇到的最大sum和。
 7         sum = Math.max(0, sum);  //每次sum的和一定要大于0,否则之前sum的数字就不要了。
 8     }
 9     return max;
10  }
11  //---------------------------------------------------------------
12   public int maxSubArray(int[] nums) {
13     int max = Integer.MIN_VALUE, sum = 0;
14     if(nums == null || nums.length  ==0) return 0;
15     int[] partMax = new int[nums.length];
16     int[] globalMax = new int[nums.length];
17     partMax[0] = globalMax[0] = nums[0];
18     
19     for(int i = 1; i < nums.length; i++) {
20         partMax[i] = Math.max(partMax[i - 1] + nums[i], nums[i]);
21         globalMax = Math.max(partMax[i], globalMax[i-1]);
22     }
23     return globalMax[nums.length - 1];
24 }
View Code

 10 分割回文串2

http://www.lintcode.com/zh-cn/problem/palindrome-partitioning-ii/#

注意点:

 1 private boolean[][] getInstance(String s) {
 2     boolean[][] str = new boolean[s.length()][s.length()];
 3     for(int i = 0; i < s.length(); i++) {
 4         str[i][i] = true;
 5     }
 6     for(int i = 0; i < s.length() - 1; i++) {
 7         str[i][i+1] = s.charAt(i) == s.charAt(i+1);
 8     }
 9     for(int len = 2;len <s.length(); len++) {
10         for(int i = 0; i + len < s.length(); i++) {
11             str[i][i+len] = str[i + 1][i+len -1] && s.charAt(i) == s.charAt(i+len);
12         }
13     }
14     return str;
15 }
16 public int minCut(String s) {
17     if(s==null || s.length() ==0) return 0;
18     boolean[][] str = getInstance(s);
19     int[] f = new int[s.length() + 1];
20     for(int i = 0; i < f.length; i++) {
21         f[i] = i - 1;
22     }
23     for(int i= 1; i <= s.length(); i++) {
24         for(int j = 0; j < i; j++) {
25             if(str[j][i-1]) {
26                 f[i]= Math.min(f[i], f[j] + 1);
27             }
28         }
29     }
30     return f[f.length -1];
31 }
5-24 简化写法

 

 1 for(int i = 0; i<f.length; i++) {  
 2         f[i] = i - 1;  //i长度的字符串,最多分割i-1刀可以构成回文串,设为Integer.MAX_VALUE也行,关键是f[0]=-1,f[1]=0
 3     }
 4     for(int i = 1; i <= s.length(); i++) { //长度为i的字符串
 5         for(int j = 0; j< i; j++) {              //两个子串: 0~j-1, j~i-1,判断是否是回文串。
 6             if(str[j][i-1]) {
 7                 f[i] = Math.min(f[i], f[j] + 1);  //f[j]已经在之前求出来了,表示0~j-1这j个字符至少分几刀可以形成回文串
 8             }
 9         }
10     }
部分解释
 1   private boolean isPalindrome(String s, int start, int end) {
 2     for(int i = start, j = end; i < j; i++,j--) {
 3         if(s.charAt(i) != s.charAt(j)) return false;        
 4     }
 5     return true;
 6 }
 7 private boolean[][] getPalindromeInstance(String s) {
 8     boolean[][] str = new boolean[s.length()][s.length()];
 9     for(int i = 0; i<s.length(); i++) {
10         str[i][i] = true;
11     }
12     for(int i = 0; i<s.length() - 1; i++) {
13         str[i][i+1] = isPalindrome(s, i, i+1);
14     }
15     for(int len = 2; len < s.length(); len++) {  //长度是len+1的子串
16         for(int i = 0; i + len < s.length(); i++) {    //len+i代表尾角标位置
17             str[i][i+len] = isPalindrome(s, i + 1, i+len - 1) && s.charAt(i) == s.charAt(i+len);
18         }
19     }
20     return str;
21 }
22 public int minCut(String s) {
23      if(s==null || s.length() == 0) return 0;
24      boolean[][] str = getPalindromeInstance(s);
25      
26      int[] f = new int[s.length() + 1];
27      for(int i = 0; i < f.length; i++) {  //长度为i的字符串最多分割i-1次就可以都是回文串,也可以将f[i]设为Integer.MAX_VALUE;
28          f[i] = i - 1;
29      }
30      for(int i = 1; i<= s.length(); i++) {//i个字符构成回文串
31         for(int j = 0; j < i; j++) {
32             if(str[j][i -1]) {
33                 f[i] = Math.min(f[i],f[j] + 1);
34             }
35         }
36      }
37      return f[f.length - 1];
38 }
View Code

 11  单词分割

http://www.lintcode.com/problem/word-break

 1 public boolean wordBreak(String s, Set<String> dict) {
 2     if(s == null || s.length() == 0) return true;
 3     if(dict == null ||dict.size() == 0) return false;
 4     int wordLen = 0;
 5     for(String s1 : dict) {
 6         wordLen = Math.max(wordLen, s1.length());
 7     }
 8     boolean f[] = new boolean[s.length() + 1];
 9     f[0] = true;
10     for(int i = 1; i <= s.length(); i++) {   //i表示包含i个单词,j表示最后一个单词的长度
11         f[i] = false;
12         //0~i-1   0~i-j-1,i-j~i-1
13         for(int j=1;j<=wordLen && j<=i; j++) {
14             if(f[i-j]) {
15                 if(dick.contains(s.subString(i-j, i-1))) {
16                     f[i] = true;
17                     break;
18                 }
19             }
20         }
21     }
22     return f[f.length - 1];
23 }
update 1
 1 public boolean wordBreak(String s, Set<String> dict) {
 2     if(s == null || dict == null) return false;
 3     if(dict.size() == 0) {
 4         if(s.length() == 0 ) return true;
 5         return false;
 6     }
 7     int maxLen = 0;
 8     for(String s1 : dict) {
 9         maxLen = Math.max(s1.length(), maxLen);
10     }
11     boolean[] canBreak = new boolean[s.length() + 1];
12     canBreak[0] = true;
13     for(int i = 1; i <= s.length(); i++) {
14         canBreak[i] = false;
15         for(int lastWordLen = 1; lastWordLen <=i && lastWordLen <= maxLen; lastWordLen++) {
16             if(canBreak[i - lastWordLen]) {    //最后一个单词的下标是 [i - lastWordLen, i) 左开右闭,包含的字符个数为lastWordLen
17                 String word = s.substring(i - lastWordLen, i); 
18                 if(dict.contains(word)) {
19                     canBreak[i] = true;
20                     break;
21                 }
22             }
23         }
24     }
25     return canBreak[s.length()];
26 }
View Code

 12 最长公共子序列  LCS

http://www.lintcode.com/zh-cn/problem/longest-common-subsequence/#

 1 public int longestCommonSubsequence(String A, String B) {
 2     if(A == null || B == null || A.length() == 0 || B.length() == 0) {
 3         return 0;
 4     }
 5     int m = A.length(), n = B.length();
 6     int[][] f = new int[m+1][n+1];
 7     for(int i = 1; i <=m; i++) {
 8         f[i][0] = 0;
 9     }
10     for(int i = 0; i <=n; i++) {
11         f[0][i] = 0;
12     }
13     for(int i = 1; i<=m; i++) {
14         for(int j =1; j<=n; j++) {
15             if(A.charAt(i-1) == B.charAt(j-1)) {
16                 f[i][j] = f[i-1][j-1]+1;
17             } else {
18                 f[i][j] = Math.max(f[i][j-1],f[i-1][j]);
19             }
20         }
21     }
22     return f[m][n];
23 }
update 1
 1     public int longestCommonSubsequence(String A, String B) {
 2     if(A == null || B == null || A.length() == 0 || B.length() == 0) return 0;
 3     int[][] lcs = new int[A.length() + 1][B.length() + 1];
 4     for(int i = 0; i <= A.length(); i++) {
 5         lcs[i][0] = 0;
 6     }
 7     for(int j = 0; j <= B.length(); j++) {
 8         lcs[0][j] = 0;
 9     }
10     for(int i = 1; i <= A.length(); i++) {
11         for(int j = 1; j <= B.length(); j++) {
12             if(A.charAt(i-1) == B.charAt(j-1)) {
13                 lcs[i][j] =  Math.max(lcs[i - 1][j - 1]+1, Math.max(lcs[i - 1][j], lcs[i][j - 1]));  //只写lcs[]][]+1即可,不用判断的
14             } else {
15                 lcs[i][j] =  Math.max(lcs[i - 1][j - 1]+0, Math.max(lcs[i - 1][j], lcs[i][j - 1]));
16             }
17         }
18     }
19     return lcs[A.length()][B.length()];
20 }
View Code

 13  最长公共子串

http://www.lintcode.com/zh-cn/problem/longest-common-substring/#

问题: contains复杂度O(n)???

注意点:

错误点: f[i][j]的含义搞不太懂,想一想递归关系之间的具体实现过程。在循环过程中,公共子串中的每一个字符都会作为最后一个字符去进行比较。

 1 public int longestCommonSubstring(String A, String B) {
 2     if(A == null || B == null || A.length() == 0 || B.length() == 0) return 0;
 3     int max = 0;
 4     for(int i = 0; i < A.length(); i++) {
 5         for(int j= i + 1; j <= A.length(); j++) {
 6             if(B.contains(A.substring(i,j))) max = Math.max(max, j- i);
 7         }
 8     }
 9     return max;                //O(n * n * n)
10  }
11 //----------------------------------------------------
12 public int longestCommonSubstring(String A, String B) {
13     if(A == null || B == null || A.length() == 0 || B.length() == 0) return 0;
14     
15     int[][] lcs = new int[A.length() + 1][B.length() + 1];
16     for(int i = 1; i <= A.length(); i++) {
17         for(int j = 1; j <= B.length(); j++) {
18             if(A.charAt(i-1) == B.charAt(j-1)) {
19                 lcs[i][j] = lcs[i - 1][j - 1]+1;
20             } else {
21                 lcs[i][j] =  0;
22             }
23         }
24     }
25     
26     int max = 0;    
27     for(int i = 1; i <= A.length(); i++) {
28         for(int j = 1; j <= B.length(); j++) {
29             max = Math.max(max, lcs[i][j]);
30         }
31     }
32     return max;
33 }
View Code

 14 编辑距离

http://www.lintcode.com/zh-cn/problem/edit-distance/#

 1  // 为什么要死记公式啊,先求lcs再去匹配一致,考虑并不周全     abc     cab  
 2  public int minDistance(String word1, String word2) {
 3     if(word1 == null || word2 == null) {
 4         if(word1 != null) return word1.length();
 5         if(word2 != null) return word2.length();
 6         return 0;
 7     }
 8     int[][] lcs = new int[word1.length() + 1][word2.length() + 1];
 9     for(int i = 1; i <= word1.length(); i++) {
10         for(int j = 1; j <= word2.length(); j++) {
11             if(word1.charAt(i-1) == word2.charAt(j-1)) {
12                 lcs[i][j] = lcs[i - 1][j - 1]+1;
13             } else {
14                 lcs[i][j] =  0;
15             }
16         }
17     }
18     int max = 0;    
19     for(int i = 1; i <= word1.length(); i++) {
20         for(int j = 1; j <= word2.length(); j++) {
21             max = Math.max(max, lcs[i][j]);
22         }
23     }
24     return Math.max(word1.length()-max, word2.length() - max);
25 }
26 //----------------------
27  public int minDistance(String word1, String word2) {
28     if(word1 == null || word2 == null) {
29         if(word1 != null) return word1.length();
30         if(word2 != null) return word2.length();
31         return 0;
32     }
33     int[][] f =  new int[word1.length() + 1][word2.length() + 1];
34     for(int i = 0; i <= word1.length(); i++) f[i][0] = i;
35     for(int j = 0; j <= word2.length(); j++) f[0][j] = j;
36     
37     for(int i = 1; i <=word1.length(); i++) {
38         for(int j = 1; j <= word2.length(); j++) {
39             if(word1.charAt(i - 1) == word2.charAt(j - 1)) {
40                 f[i][j] = Math.min(Math.min(f[i-1][j] + 1, f[i][j-1]+1),f[i- 1][j - 1]);
41             } else {
42                 f[i][j] = Math.min(Math.min(f[i-1][j] + 1, f[i][j-1]+1),f[i- 1][j - 1] + 1);
43             }
44         }
45     }
46     return f[word1.length()][word2.length()];
47  }
View Code

 

链表----------------------------------------------------------------------------------------

注意事项: 调用node.next时,一定要确保node非null,否则空指针异常。

     链表的head 和head.next是否为空先判断下,类似二叉树root要单独拿出来考虑一样。

 1 链表的基本操作
 2 1. Insert a Node in Sorted List
 3 2. Remove a Node from Linked List
 4 3. Reverse a Linked List
 5 4. Merge Two Linked Lists
 6 5. Middle of a Linked List
 7 
 8 1.  // 最简单的方法
 9     private ListNode reverse(ListNode head) {
10         if(head == null || head.next == null) return head;
11         ListNode prev = null;
12         while(head!= null ) {
13             ListNode temp = head.next;
14             head.next = prev;
15             prev = head;
16             head = temp;
17         }
18         return prev;
19     }
20     //另一种写法
21  private ListNode reverse(ListNode head) {
22      if(head == null || head.next == null) return head;
23      ListNode tail = head;
24      ListNode next =tail.next;
25      while(next != null) {
26          ListNode temp = next.next;
27          next.next =tail;
28         tail = next;
29         next =temp;
30      }        
31      head =tail;
32      tail.next = null;
33      return head;
34  }
35 4. private ListNode merge(ListNode left, ListNode right) {
36     ListNode dummy = new ListNode(0), tail = dummy;
37     while(left != null && right != null) {
38         tail.next = left;
39         left = left.next;
40         tail = tail.next;
41         tail.next = right;
42         right.next = right;
43         tail = tail.next;
44     }
45     if(left != null) tail.next = left;
46     else tail.next = right;
47     return dummy.next;
48 }
49 5.   快慢指针
50     private ListNode getMid(ListNode head) {}
51      //12345  要找到3
52      if(head == null || head.next == null) return head;
53      ListNode slow = head, fast = head;
54      while(fast.next != null && fast.next.next != null) {
55          slow = slow.next;
56          fast = fast.next.next;
57      }
58      return slow;
59     //查找倒数第n个结点
60     private ListNode find(ListNode head) {
61           ListNode slow = head, fast = head;
62     // 1 2 3 4 5  找4,倒数第2个,需要在fast走第二步的时候,slow开始走第一步
63     int i = 0;
64     while(fast.next != null) {
65         i++;
66         fast = fast.next;
67         if(i < 2) coutinue;
68         slow = slow.next;
69     }
70     return slow;
71     }
链表基本操作

 

1  删除排序链表2

http://www.lintcode.com/zh-cn/problem/remove-duplicates-from-sorted-list-ii/

 1 //----------------运行超时
 2   public static ListNode deleteDuplicates(ListNode head) {
 3         // write your code here
 4         if(head == null || head.next == null) return head;
 5         ListNode prev = null;
 6         ListNode curr = head;
 7         Map<ListNode,Integer> map = new HashMap<ListNode,Integer>();
 8         int value = 0;
 9         while(curr != null) {
10             if(map.get(curr) != null) {
11                 map.put(curr,map.get(curr) + 1);
12             } else {
13                 map.put(curr,1);
14             }
15         }
16         prev.next = head;
17         curr = head;
18         ListNode currNext = curr.next;
19         while(currNext != null) {
20             if(map.get(currNext) != 1) {
21                 curr = currNext;
22                 currNext.next = currNext.next;
23             }
24         }
25         return prev.next;
26     }
27 //--------------------------------------------------
28  public static ListNode deleteDuplicates(ListNode head) {
29      if(head == null || head.next == null) return head;
30      ListNode dummy = new ListNode(0);
31      dummy.next = head;
32      //只要不用next操作,引用再怎么换也不会影响链表。
33      head = dummy;
34      while(head.next != null && head.next.next != null) {
35          if(head.next.val == head.next.next.val) {
36              int val = head.next.val;
37              while(head.next != null && head.next.val == val) {
38                  head.next = head.next.next;
39              }
40          } else {
41              head = head.next;
42          }
43      }
44      return dummy.next;
45  }
View Code

2   删除排序链表

http://www.lintcode.com/zh-cn/problem/remove-duplicates-from-sorted-list/#

注意点:引入dummy的目的是为了不用将头结点删除与否分情况讨论。这里头结点肯定不用删除,所以可以不引入dummy。

            也可以沿用删除链表2的解法,稍微改改。

 1  public static ListNode deleteDuplicates(ListNode head) { 
 2         // write your code here
 3         if(head == null || head.next == null) return head;
 4         ListNode dummy = new ListNode(0);
 5         dummy.next = head;
 6         head = dummy;
 7         while(head.next != null && head.next.next != null) {
 8             if(head.next.val == head.next.next.val) {
 9                 head.next = head.next.next;
10             } else head = head.next;
11         }
12         return dummy.next;
13     }  
View Code

3  反转链表

http://www.lintcode.com/zh-cn/problem/reverse-linked-list/

注意点: 死记解法,四步骤

 1  public ListNode reverse(ListNode head) {
 2         // write your code here
 3        ListNode prev = null;
 4        while(head != null) {
 5            ListNode temp = head.next;
 6            head.next = prev;
 7            prev = head;
 8            head = temp;
 9        }
10        return prev;
11     }
View Code

4   反转链表2

http://www.lintcode.com/zh-cn/problem/reverse-linked-list-ii/

错误点: 第二个for循环里写成了if(nPost.next== null) return null;

注意点: 第二个for循环里,n~m ,共n-m+1个数字,需要nNode走n-m次,i=m+1时,n移动了一次,所以i最后出了循环需要等于m+n-m = n

 1 public ListNode reverseBetween(ListNode head, int m , int n) {
 2       if(head == null || m >= n) return head;
 3       ListNode dummy = new ListNode(0);
 4       dummy.next = head;
 5       head = dummy;
 6       for (int i = 1; i < m; i++) {
 7           if(head != null) head = head.next;
 8           else return null;
 9       }
10       ListNode mprev = head;
11       ListNode mNode = mprev.next;
12       ListNode nNode = mNode;
13       ListNode nPost = nNode.next;
14       for(int i = m; i < n;i++) {
15           if(nPost == null) return null;
16           ListNode temp = nPost.next;
17           nPost.next = nNode;
18           nNode = nPost;
19           nPost = temp;
20       }
21       mprev.next = nNode;
22       mNode.next = nPost;
23       return dummy.next;
24       
25   }
View Code

5  链表划分

http://www.lintcode.com/zh-cn/problem/partition-list/

注意点: 将链表分成两个子链,左链放比指定数小的,右链连比指定数大的,最后再将他们合并。

     leftDummy和rightDummy保持不动,作为头指针,然后从它们的位置发出left和right指针,作为尾指针,依次移动记录当前子链表的最后一个位置。

      头指针.next=头结点,尾指针=尾结点

 1 public ListNode partition(ListNode head, int x) {
 2        if(head == null) return head;
 3        ListNode leftDummy =  new ListNode(0);
 4        ListNode rightDummy =  new ListNode(0);
 5        ListNode left = leftDummy, right = rightDummy;
 6        while(head != null) {
 7            if(head.val < x) {
 8                left.next = head;
 9                left = head;
10            } else {
11                right.next = head;
12                right = head;
13            }
14            head = head.next;
15        }
16        right.next = null;
17        left.next = rightDummy.next;
18        return leftDummy.next;
19    }
View Code

 6  链表排序

http://www.lintcode.com/zh-cn/problem/sort-list/#

注意点: 

错误点: sortList(ListNode head) 里if(head == null )而不判断head.next会报错,为啥??????

 1   private ListNode findMid(ListNode head) {
 2         ListNode slow = head, fast = head.next;
 3         while(fast.next != null && fast.next.next != null) {
 4             fast = fast.next.next;
 5             slow = slow.next;
 6         }
 7         return slow;
 8         //  12345   return 2;
 9    }
10    private ListNode merge(ListNode head1, ListNode head2) {
11        //dummy是合并后主链表的头,tail是尾。head1或head2中每当有一个结点链入主链,那链入的那个结点就可以
12        //在原先的链表中删除了,同时把原先的链表的头往后移。因为主链中加入了一个结点,所以主链的tail后移一次。
13        ListNode dummy = new ListNode(0), tail = dummy;
14        while(head1 != null && head2 != null) {
15            if(head1.val < head2.val) {
16                tail.next = head1;
17                head1 = head1.next;
18            } else {
19                tail.next = head2;
20                head2 = head2.next;
21            }
22            tail = tail.next;
23        }
24        //head1或head2有一个都链入主链后,把另一个非空的原先链表在链到主链尾部
25        //(这时原先链表中的后面位置的结点并没有进行排序。)
26        //最后返回的结果只是将head1或者head2进行排序了。(head1为空,则代表它完成排序了)
27        //要保证最后都有序,则head1和head2必须先有序。
28        if(head1 != null) {
29            tail.next = head1;
30        } else {
31            tail.next = head2;
32        }
33        return dummy.next;
34    }
35    
36    public ListNode sortList(ListNode head) {
37        if(head == null || head.next == null) return head;
38        ListNode mid = findMid(head);
39        ListNode right = sortList(mid.next);
40        mid.next = null; 
41        ListNode left = sortList(head);
42        return merge(left, right);
43     }
merge排序

7      重排链表

http://www.lintcode.com/zh-cn/problem/reorder-list/#

 1 public void reorderList(ListNode head) {  
 2        if(head == null || head.next == null) return;
 3        ListNode mid = getMid(head);
 4        ListNode right = reverse(mid.next);
 5        mid.next = null;
 6        head = merge(head, right);        
 7     }
 8     
 9 private ListNode getMid(ListNode head) {}
10     //12345   15243 要找到3
11     if(head == null || head.next == null) return head;
12     ListNode slow = head, fast = head;
13     while(fast.next != null && fast.next.next != null) {
14         slow = slow.next;
15         fast = fast.next.next;
16     }
17     return slow;
18 }
19 private ListNode reverse(ListNode head) {
20     if(head == null || head.next == null) return head;
21     
22     ListNode prev = null;
23     while(head!= null ) {
24         ListNode temp = head.next;
25         head.next = prev;
26         prev = head;
27         head = temp;
28     }
29     return prev;
30 }
31 private ListNode merge(ListNode left, ListNode right) {
32     ListNode dummy = new ListNode(0), tail = dummy;
33     while(left != null && right != null) {
34         tail.next = left;
35         left = left.next;
36         tail = tail.next;
37         tail.next = right;
38         right = right.next;
39         tail = tail.next;
40     }
41     if(left != null) tail.next = left;
42     else tail.next = right;
43     return dummy.next;
44 }
View Code

8    带环链表

http://www.lintcode.com/zh-cn/problem/linked-list-cycle-ii/#

注意点:快慢指针

 1 public ListNode detectCycle(ListNode head) {  
 2     if(head == null || head.next == null) return null;
 3     ListNode slow1 = head, fast = head;
 4     while(fast.next != null && fast.next.next != null) {
 5         slow1= slow1.next;
 6         fast = fast.next.next;
 7         if(slow1 == fast) {
 8             ListNode slow2 = head;
 9             while(true) {
10                 if(slow1 == slow2) return slow1;
11                 slow2 = slow2.next;
12                 slow1 = slow1.next;
13             }
14         }
15     }
16     return null;
17 }
View Code

 9  旋转链表

http://www.lintcode.com/zh-cn/problem/rotate-list/#

 1  public ListNode rotateRight(ListNode head, int k) {
 2         if(head == null || head.next == null || k == 0) return head;
 3         int len = 0;
 4         ListNode temp = head;
 5         while( temp != null ) {
 6             len++;
 7             temp = temp.next;
 8         }
 9         k = k % len;
10         if(k == 0) return head;
11         ListNode tail= head;
12         int i = 1;
13         while( len - k != i) {
14             i++;
15             tail = tail.next;
16         }
17         ListNode newHead = tail.next, temp1 = newHead;
18         tail.next = null;
19         while(temp1.next != null) {
20             temp1 = temp1.next;
21         }
22         temp1.next = head;
23         return newHead;
24     }
25    //----------------------------------------------------
26     private int getLength(ListNode head) {
27         int length = 0;
28         while (head != null) {
29             length ++;
30             head = head.next;
31         }
32         return length;
33     }
34     
35     public ListNode rotateRight(ListNode head, int n) {
36         if (head == null) {
37             return null;
38         }
39         
40         int length = getLength(head);
41         n = n % length;
42         
43         ListNode dummy = new ListNode(0);
44         dummy.next = head;
45         head = dummy;
46         
47         ListNode tail = dummy;
48         //寻找倒数第n个结点(类似快慢指针实现的)
49         for (int i = 0; i < n; i++) {
50             head = head.next;
51         }  
52         while (head.next != null) {
53             tail = tail.next;
54             head = head.next;
55         }
56         
57         head.next = dummy.next;
58         dummy.next = tail.next;
59         tail.next = null;
60         return dummy.next;
61     }
View Code

 10   合并k个排序链表

http://www.lintcode.com/zh-cn/problem/merge-k-sorted-lists/

 1 //两两合并----------------------------------------------
 2     public ListNode mergeKLists(List<ListNode> lists) {  
 3         if(lists == null || lists.size() == 0) return null;
 4         
 5         while(lists.size() > 1) {
 6             List<ListNode> newList = new ArrayList<ListNode>();
 7             for(int i = 0; i + 1< lists.size() ; i+=2) {
 8                 ListNode dummy = new ListNode(0);
 9                 dummy.next = mergeTwo(lists.get(i), lists.get(i+1));
10                 newList.add(dummy.next);
11             }
12             if(lists.size() % 2 != 0) newList.add(lists.get(lists.size() - 1));
13             lists = newList;
14         }
15         return lists.get(0);
16     }
17     
18     private ListNode mergeTwo(ListNode node1, ListNode node2) {
19         ListNode dummy = new ListNode(0), tail = dummy;
20         while(node1 != null && node2 != null) {
21             if(node1.val < node2.val) {
22                 tail.next = node1;
23                 node1 = node1.next;
24             } else {
25                 tail.next = node2;
26                 node2 = node2.next;
27             }
28             tail = tail.next;
29         }
30         if(node1 != null) {
31             tail.next = node1;
32         } else {
33             tail.next = node2;
34         }
35         return dummy.next;
36     }
37     //分治-------------------------------------------------
38      public ListNode mergeKLists(List<ListNode> lists) {  
39         if(lists == null || lists.size() == 0) return null;
40         return mergeHelper(lists, 0, lists.size() - 1);
41      }
42      private ListNode mergeHelper(List<ListNode> lists, int start , int end) {
43          if(start == end) return lists.get(start);
44          int mid = start + (end - start) / 2;
45          ListNode left = mergeHelper(lists, start, mid);
46          ListNode right = mergeHelper(lists, mid+1, end);
47          return mergeTwo(left, right);
48      }
49      
50     private ListNode mergeTwo(ListNode node1, ListNode node2) {
51         ListNode dummy = new ListNode(0), tail = dummy;
52         while(node1 != null && node2 != null) {
53             if(node1.val < node2.val) {
54                 tail.next = node1;
55                 node1 = node1.next;
56             } else {
57                 tail.next = node2;
58                 node2 = node2.next;
59             }
60             tail = tail.next;
61         }
62         if(node1 != null) {
63             tail.next = node1;
64         } else {
65             tail.next = node2;
66         }
67         return dummy.next;
68     }
View Code

11   复制随机指针链表

http://www.lintcode.com/zh-cn/problem/copy-list-with-random-pointer/#

注意点:传入head并在另一个函数中操作时,并不会引起传入前的head的变化。 

    见答案,不需要返回值  http://www.jiuzhang.com/solutions/copy-list-with-random-pointer/

 1   public RandomListNode copyRandomList(RandomListNode head) {
 2         if(head == null) return head;
 3          head = insert(head);
 4         RandomListNode dummy = new RandomListNode(0);
 5         dummy.next = head;
 6         while(head != null) {
 7             if(head.random == null) {
 8                 head.next.random = null;
 9             } else {
10                 head.next.random = head.random.next;
11             }
12             head = head.next.next;
13         }
14         dummy.next = remove(dummy.next);
15         return dummy.next;
16         
17     }
18     private RandomListNode insert(RandomListNode head) {
19         if(head == null) return head;
20         RandomListNode dummy = new RandomListNode(0);
21         dummy.next = head;
22         while(head != null) {
23             RandomListNode temp = new RandomListNode(head.label);
24             temp.next = head.next;
25             head.next = temp;
26             head = head.next.next;
27         }
28         return dummy.next;
29     }
30     private RandomListNode remove(RandomListNode head) {
31         RandomListNode dummy = new RandomListNode(0);
32         dummy.next = head.next;
33         while(head.next.next != null) {
34             RandomListNode temp = head.next.next;
35             head.next.next = head.next.next.next;
36             head = temp;
37         }
38         return dummy.next;
39     }
View Code

 //-----------------------------------------------------------------------------------------------------------------

Arrays      拿到数组先排序,最快需要nlogn.(快排,归并,堆排),然后看看排序是否有助于问题解决,是否满足复杂度要求。

    数组和的问题,排序后,收尾指针依次中间移动,可以以O(n)的代价,遍历一次就能判断是否满足。

1    合并排序数组

注意点:可以从头开始合并,也可以从尾开始合并

http://www.lintcode.com/zh-cn/problem/merge-sorted-array/

 1  public void mergeSortedArray(int[] A, int m, int[] B, int n) {
 2        int index = m+n-1, i = m - 1, j = n - 1;
 3        while(i >=0 && j >=0) {
 4            if(A[i] > B[j]) {
 5                A[index--] = A[i--]; 
 6               
 7            } else {
 8                A[index--] = B[j--]; 
 9            }
10        }
11        while(i >= 0) {
12            A[index--] = A[i--]; 
13        } 
14        while(j >= 0) {
15            A[index--] = B[j--]; 
16        }
17        
18     }
View Code

 2  两个排序数组的中位数

http://www.lintcode.com/zh-cn/problem/median-of-two-sorted-arrays/

注意点:找中点,就是找第k个数,依次剔除k/2, k/4,......1个数,剩下的就是要找的数。

              如果k个排序数组找中位数,则二分答案,判断此答案是否位于中间。

错误点: 需要double,则return时除的时候要 /2.0 而不是  /2

 1 //  A = 2 3 4 5 6 7
 2  //  B = 1
 3  // 找中点,第k = 4大的数,则先去掉 k/2 = 2 个数,之后再从剩下的数中找第k-k/2 = 2大的数。
 4  //                             去2个数时,由于B不包含2个数,所以把A的前2个数去掉,剩下: 4 5 6 7  和 1;  
 5  // 从它们中找第2大的数就是结果。去掉的数不一定非要是A,B中最小的前几个数,只要保证去掉的数比要找的数小,那要找的数的相对位置就不会变。
 6  // 在4 5 6 7  和 1中找第2个大的数时,先去掉1个数,在从剩下的里面找第一个大的数就是结果。所以把1去掉,剩下了4 5 6 7 。这时第1个大的数是4,也就是最后结果。
 7  
 8  public double findMedianSortedArrays(int[] A, int[] B) {
 9     int len = A.length + B.length;
10     if(len % 2 == 1) return findKth(A, 0, B, 0, len/2+1);
11     else return (findKth(A, 0, B, 0, len/2) + findKth(A, 0, B, 0, len/2+1)) / 2.0;
12 }
13 //函数含义:A数组从AStart角标开始,B从BStart开始,寻找A,B中第k个大的数
14 private int findKth(int[] A, int AStart, int[] B, int BStart, int k) {
15     if(AStart >= A.length) return B[BStart + k - 1];
16     if(BStart >= B.length) return A[AStart + k - 1];
17     
18     if(k == 1) {
19         return Math.min(A[AStart], B[BStart]);
20     }
21     
22     //找第k个,先去掉前k/2个数,AValue和BValue不可能都是MAX_VALUE
23     int AValue = AStart + k/2 - 1 < A.length ? A[AStart + k/2 - 1] : Integer.MAX_VALUE;
24     int BValue = BStart + k/2 - 1 < B.length ? B[BStart + k/2 - 1] : Integer.MAX_VALUE;
25     if(AValue <= BValue) {
26         //去A的前k/2个数,则去掉后的角标从AStart+k/2开始
27         return findKth(A, AStart+k/2, B, BStart, k - k/2);  //递归的终止条件是k-k/2=1,一定会走到1,因为1+2+...+ k/2 = k - 1 k是偶数,1+1+2+...+ k/2 = k - 1 k是奇数
28     } else {
29         return findKth(A, AStart, B, BStart + k/2, k - k/2);
30     }
31 }
View Code

3  最大子数组2

http://www.lintcode.com/zh-cn/problem/maximum-subarray-ii/

衍生:最小子数组  http://www.lintcode.com/zh-cn/problem/minimum-subarray/#   把数组取反,求出最大子数组,再把结果取反即可。

   最大子数组差   http://www.lintcode.com/zh-cn/problem/maximum-subarray-difference/  左右求出最大最小子数组,因为不许重叠,所以找分割线依次比较。

错误点:a=1,b=2;错,要写成a=1;b=2;

    int a =1, b = 2; 可以

注意点:见答案

 1 //最大子数组答案    http://www.lintcode.com/zh-cn/problem/maximum-subarray/   
 2  public int maxSubArray(int[] nums) {
 3     if(nums == null || nums.length == 0) return 0;
 4     int sum = 0, preFixSum = 0, max = Integer.MIN_VALUE;
 5     //理解不了的话,只需要知道这个操作能实现功能就行,死记代码
 6     for(int i = 0; i< nums.length; i++) {
 7         sum+= nums[i];
 8         max = Math.max(max, sum - preFixSum);
 9         preFixSum = Math.min(preFixSum, sum);
10     }
11     return max;
12  }
13  
14  public int maxTwoSubArrays(List<Integer> nums) {
15      if(nums == null || nums.size() <= 1) return 0;
16      // i是分割线位置,i+1就是分割线之后的第一个位置的坐标
17      int result = Integer.MIN_VALUE;
18      for(int i = 0; i < nums.size() - 1; i++) {
19          int max1 = Integer.MIN_VALUE, max2 = max1;
20          int sum1 = 0, sum2 = 0, preFix1 = 0, preFix2 = 0;
21          for(int j = 0; j <=i; j++) {
22              sum1+=nums.get(j);
23              max1 = Math.max(max1, sum1 - preFix1);
24              preFix1 = Math.min(preFix1, sum1);
25          }
26          for(int j = i+1; j < nums.size(); j++) {
27              sum2+=nums.get(j);
28              max2 = Math.max(max2, sum2 - preFix2);
29              preFix1 = Math.min(preFix2, sum2);
30          }
31          result = Math.max(result, max1+max2);
32      }
33      return result;
34  }
35  //O(n)---------------------------------------------
36   public int maxTwoSubArrays(List<Integer> nums) {
37       int[] left = new int[nums.size()];
38       int[] right = new int[nums.size()];
39       int sum = 0, preFixSum = 0, max = Integer.MIN_VALUE;
40       for(int i = 0; i< nums.size(); i++) {
41           sum+= nums[i];
42           max = Math.max(max, sum - preFixSum);
43           preFixSum = Math.min(preFixSum, sum);
44           left[i] = max;
45       }
46       sum = 0, preFixSum = 0, max = Integer.MIN_VALUE;
47       for(int i = nums.size() - 1; i >= 0; i--) {
48           sum+= nums[i];
49           max = Math.max(max, sum - preFixSum);
50           preFixSum = Math.min(preFixSum, sum);
51           right[i] = max;
52       }
53       int result = Integer.MIN_VALUE;
54       for(int i = 0; i < nums.size() - 1; i++) {
55           result = Math.max(result, left[i] + right[i+1]);
56       }
57       return result;
58   }
View Code

4  买卖股票的最佳时机

http://www.lintcode.com/zh-cn/problem/best-time-to-buy-and-sell-stock/

http://www.lintcode.com/zh-cn/problem/best-time-to-buy-and-sell-stock-ii/

http://www.lintcode.com/zh-cn/problem/best-time-to-buy-and-sell-stock-iii/#

 注意点:包含DP

错误点:  ①profit = Math.max(profit, i - min);

           ②min = Math.min(min, i);            一二前后顺序的区别是是否每一轮至少要包含一个数。此题中盈利的计算,一开始是买入,没有盈利,所以也即一个数都不能包含,

                   所以要先②后①。

 1 //错误逻辑,思路都理不清,代码更写不出来。 
 2  public int maxProfit(int[] prices) {
 3     if(prices == null || prices.length <= 1) return 0;
 4     int profit = 0, min = 0;
 5     for(int i : prices) {
 6         min = Math.min(min, i);
 7         profit + =  i - min;    
 8     }
 9     return profit;
10 }
11 // 当天有盈利,代表着当天卖出和前一天买入。连续三天盈利,每隔天的买入卖出正好合下来是三天前买入,三天后卖出的情况。 1    2    3    4
12 public int maxProfit(int[] prices) {
13     int profit = 0;
14     for(int i = 0; i < prices.length- 1; i++) {
15         int diff = prices[i + 1] - prices[i];
16         if(diff > 0) profit += diff;
17     }
18     return profit;
19 }
update1

 

 1  //-----------------------------------------------------------
 2     //  暴力破解
 3      public int maxProfit(int[] prices) { 
 4         if(prices == null || prices.length == 0) return 0;
 5         int max =0 ;
 6         for(int i = 1; i< prices.length; i++) {
 7             int sum = 0;
 8             for(int j = 0; j < i; j++) {            
 9                 max= Math.max(max, prices[i] - prices[j]);
10             }            
11         }
12         return max;
13    }
14  //------------------------------------------------------
15    public int maxProfit(int[] prices) { 
16       if(prices == null || prices.length == 0) return 0;
17       int min = Integer.MAX_VALUE, profit = 0;
18       for(int i : prices) {
19           min = Math.min(i, min);   // min = i < min ? i : min;
20           profit = Math.max(i - min, profit);
21       }
22       return profit;
23    }
24    
25 //股票二------------------------------------------
26 public int maxProfit(int[] prices) {
27     int profit = 0;
28     for(int i = 0; i < prices.length- 1; i++) {
29         int diff = prices[i + 1] - prices[i];
30         if(diff > 0) profit += diff;
31     }
32     return profit;
33 }
34 
35 //股票三-----------------------------------------------
36 public int maxProfit(int[] prices) {
37     if (prices == null || prices.length <= 1) {
38             return 0;
39         }
40 
41     int[] left = int[prices.length];
42     int[] right = int[prices.length];
43     
44     //从左往右看,不依赖于右侧,能卖出的最大利润。通过更新买入的最小值(min)来计算  DP
45     int min = prices[0], left[0] = 0;
46     for(int i = 1; i < prices.length; i++) {
47         min = math.min(min, prices[i]);
48         left[i] = Math.max(left[i - 1], prices[i] - min);
49     }
50     
51     //从右往左看,不依赖于左侧,能卖出的最大利润。通过更新卖出的最大值(max)来计算
52     int max = prices[prices.length - 1], right[prices.length - 1] = 0;
53     for(int i = prices.length -2; i>=0; i--) {
54         max = Math.max(prices[i], max);
55         right[i] = Math.max(right[i + 1], max - prices[i]);
56     }
57     
58     //类似分割线,left和right不交叉
59     int maxProfit = 0;
60     for(int i = 0; i < prices.length; i++) {
61         maxProfit = Math.max(maxProfit, left[i] + right[i]);
62     }
63     return maxProfit;
64 }
View Code

 5  两数和

http://www.lintcode.com/zh-cn/problem/two-sum/

衍生: 三数和  http://www.lintcode.com/zh-cn/problem/3sum/ 

    4数    http://www.lintcode.com/zh-cn/problem/4sum/ 

注意点:时间复杂度的计算:

      排序模块的最优复杂度nlogn,找两数和的复杂度n,所以合并的复杂度是nlogn,即用这种方法的复杂度为nlogn。

      如果放入map中,遍历一次数组,复杂度n,判断map是否包含,n,所以最后合并的复杂度n。

 1 //O(n * n)---------------------------------------------------------------
 2  public int[] twoSum(int[] numbers, int target) { 
 3     if(numbers == null || numbers.length == 0) return new int[]{-1, -1};
 4     for(int i = 0; i < numbers.length - 1; i++) {
 5         for(int j = i +1; j < numbers.length; j++) {
 6             if(numbers[i] + numbers[j] == target) return new int[]{i +1, j+1};
 7         }
 8     }
 9     return new int[]{-1, -1};
10     
11  //O(nlogn)--------------------------
12 public int[] twoSum(int[] numbers, int target) { 
13     //先排序,获得排序数组nlogn,下面的操作是O(n),最后总体的时间复杂度nlogn.
14     if(numbers == null || numbers.length <=1) return new int[]{-1, -1};
15     for(int i = 0, j = numbers.length - 1; i < j;) {
16         if(numbers[i] + numbers[j] == target) return new int[]{i + 1,j + 1};
17         else if ( numbers[i] + numbers[j] < target) i++;
18         else j--;
19     }
20     return new int[]{-1, -1};
21 
22 }
23 //O(n)------------------------------
24 public int[] twoSum(int[] numbers, int target) { 
25     if(numbers == null || numbers.length == 0) return null;
26     Map<Integer, Integer> map = new HashMap<Integer, Integer>();
27     for(int i = 0; i < numbers.length; i++) {    
28         if(map.containsKey(numbers[i])) {
29             return new int[] {map.get(numbers[i]) + 1, i+1};
30         }
31         map.put(target - numbers[i], i);
32     }
33     return null;
View Code

 6  数组划分 (类似快排)

http://www.lintcode.com/zh-cn/problem/partition-array/#

衍生:  http://www.lintcode.com/zh-cn/problem/sort-letters-by-case/        Character.isUpperCase()  

     http://www.lintcode.com/zh-cn/problem/sort-colors/  

     http://www.lintcode.com/zh-cn/problem/sort-colors-ii/    (相当于给定k个不同的数的快排)

 1 //报错,rainb里不设置startColo会排序出问题,所以这种换位的快排操作到底会产生什么结果?----------------------------------------------
 2 public void sortColors2(int[] colors, int k) {
 3      if (colors == null || colors.length == 0) {
 4             return;
 5         }
 6     rainbowSort(colors, 0, colors.length - 1);
 7 
 8 }
 9     
10 private void rainbowSort(int[] colors, int start, int end) {
11     if(colors == null || colors.length <= 1) return;
12     if(start >= end) return;
13     int mid = start + (end - start) / 2;
14     int k = colors[mid];
15     int i = start, j = end;
16     while(i <= j) {
17         while(i <=j && colors[i] < k) i++;
18         while(i <=j && colors[j] >= k) j--;
19         if(i <= j) {
20             int temp = colors[i];
21             colors[i] = colors[j];
22             colors[j] = temp;
23             i++;
24             j--;
25         }
26     }
27     rainbowSort(colors, start, i - 1);
28     rainbowSort(colors,i + 1, end);
29 } 
30 //能用--------------------------------------------------------------------------------- 
31  public void sortColors2(int[] colors, int k) {
32      if (colors == null || colors.length == 0) {
33             return;
34         }
35     rainbowSort(colors, 0, colors.length - 1, 1,k);
36 
37 }
38     
39 private void rainbowSort(int[] colors, int start, int end, int startColor, int endColor) {
40      if (startColor == endColor) {
41             return;
42         }
43     if(colors == null || colors.length <= 1) return;
44     if(start >= end) return;
45     int midColor = (startColor + endColor)/2;
46     int i = start, j = end;
47     while(i <= j) {
48         //为啥??????????????
49         //这里必须 <= midColor, 不能是<
50         while(i <=j && colors[i] <=  midColor) i++;
51         while(i <=j && colors[j] >  midColor) j--;
52         if(i <= j) {
53             int temp = colors[i];
54             colors[i] = colors[j];
55             colors[j] = temp;
56             i++;
57             j--;
58         }
59     }
60     //这里必须是midColor,不能是midColor+1
61     rainbowSort(colors, start, i, startColor,  midColor);
62     rainbowSort(colors,i,end,  midColor+1, endColor);
63 }
sort color 2

注意点: 两个指针一首一尾遍历数组        

    死记住程序,条件统一写成 i <= j  :这样返回的 i 始终是第一个大于等于k的位置,也正是题目所求。

    if(i <= j) 调制完顺序后,i++,j--一下,减少下一次while里的操作。

数组划分
 1   public int partitionArray(int[] nums, int k) {
 2         if(nums == null | nums.length <= 0) return -1;
 3         int i = 0, j = nums.length - 1;
 4         while(i <= j) {
 5             while(nums[i] < k) i++;
 6             while(nums[j] >= k) j--;
 7             if(i <= j) {
 8                 int temp = nums[j];
 9                 nums[j] = nums[i];
10                 nums[i] = temp;
11             }
12         }
13         return i;
14    }

 7 最接近零的子数组和

http://www.lintcode.com/en/problem/subarray-sum-closest/

问题:最后利用减前缀和求结果的时候,怎么知道这样的结果就离0最近? 难道是因为后一个肯定比前一个大,所以相减的结果一定大于0,最小的那个就是最接近0的?确实是这样。

      -1,-3, -3,-2,1,4,;

 -1位置补0     -1,-3, -3,-2,1,4,   前缀和    -1,-4,-7,-9,-8,-4,排序后:-9,-8,-7,-4,-4,-1。

 子数组一共有O(n * n)个,这里两两相减也就O(n)个,不能全覆盖啊?

注意点:  实现Comparator比较器接口时,虽然接口中有俩抽象方法,但只需要实现compare方法就行,equals方法不用覆盖。

     此题对应的解法,在数组中有0时,会返回两次0的角标作为返回结果。

错误点: new int[]{0,1}  ,不要写错new int[2]{}

 1  class Pair {
 2      //记录前几个数的和
 3      int sum;
 4      int index;
 5      public Pair(int s, int i) {
 6          this.sum = s;
 7          this.index = i;
 8      }
 9  }
10  
11  public class Solution {
12  
13      public int[] subarraySumClosest(int[] nums) { 
14         if(nums == null || nums.length == 0) return null;
15         if(nums.length == 1) return new int[]{0, 0};
16         //结果集数组
17         int[] res = new int[2];
18         
19         int len = nums.length;
20         //遍历一次nums,获得Pair数组,其中,前0个数的和是0
21         Pair[] sums = new Pair[len + 1]; 
22         sums[0] = new Pair(0,0);
23         for(int i = 1; i <= len; i++) {
24             sums[i] = new Pair(sums[i - 1].sum + nums[i - 1], i);
25         }
26         
27         Arrays.sort(sums, new  Comparator<Pair>(){
28             public int compare(Pair p1, Pair p2) {
29                 return p1.sum - p2.sum;
30             }
31         });
32         
33         //排序完成后,遍历sums数组,找到离0最近的子数组,从角标1开始。
34         int ans = Integer.MAX_VALUE; //answer
35         for(int i = 1; i <= len; i++) {
36             if(ans > sums[i].sum - sums[i - 1].sum) { 
37                 ans = sums[i].sum - sums[i - 1].sum;
38                 //Pair 记录的是前几个数的和,前0,1,2个等等,对应nums中的角标需要-1;
39                 int[] temp = new int[]{sums[i].index - 1, sums[i - 1].index - 1};
40                 Arrays.sort(temp);
41                 //前5个数的和-前3个数的和离0最近,则需要返回的是第4,第5个的角标,所以temp[0]+1;
42                 res[0] = temp[0] + 1; 
43                 res[1] = temp[1];
44             }
45         }
46         return res;
47      }
48  }
View Code

 8 子数组之和(求子数组,先写出来前缀和,sum(i,j) = sum(j) - sum(i - 1),然后看它和所求的关系)

http://www.lintcode.com/zh-cn/problem/subarray-sum/

注意点:子数组和为0,代表存在位置,sum(j) 等于sum(i-1)。

       既然需要sum(i - 1),那为了求0位置的和同时能用到上面的递推关系,所以在-1位置放一个0;

      两sum相等,相当于去重,hash表天然就是实现是否存在,相等问题的,所以使用hashMap存放数据。

 1 public ArrayList<Integer> subarraySum(int[] nums) {
 2       if(nums == null || nums.length == 0) return null;
 3       ArrayList<Integer> res = new ArrayList<Integer>();
 4       Map<Integer, Integer> map = new HashMap();
 5       map.put(0, -1);
 6       int sum = 0;
 7       for(int i = 0; i < nums.length; i++) {
 8           sum += nums[i];
 9           if(map.get(sum) != null) {
10               res.add(map.get(sum) + 1);
11               res.add(i);
12               return res;
13           }
14           map.put(sum, i);
15       }
16       return null;
17   }
View Code

 

数据结构

1 带最小值操作的栈

http://www.lintcode.com/zh-cn/problem/min-stack/#

注意点: 用另一个栈依次记录最小值。

 1 public class MinStack {
 2  
 3     //minStack的构造放到构造函数中比较好。
 4    Stack<Integer> minStack = new Stack<Integer>();
 5    Stack<Integer> s ;
 6     
 7     public MinStack() {
 8         // do initialize if necessary
 9        s = new Stack<Integer>();
10     }
11 
12     public void push(int number) {
13         // write your code here
14         s.push(number);
15         if(minStack.isEmpty() || minStack.peek() >= number) minStack.push(number);
16     }
17 
18     public int pop() {
19         // write your code here
20         int number = s.pop();
21         if(number == minStack.peek()) minStack.pop();
22         return number;
23     }
24 
25     public int min() {
26         // write your code here
27         
28         return minStack.peek();
29     }
30 }
View Code

 

2 用栈实现队列 

http://www.lintcode.com/zh-cn/problem/implement-queue-by-two-stacks/#

3 直方图最大矩形覆盖(栈)

http://www.lintcode.com/zh-cn/problem/largest-rectangle-in-histogram/#

注意点: 递增栈,每次角标出栈时才计算对应角标高度的直方图面积。(while循环里,栈内弹出一个数需要O(1),弹出n个数需要O(n),所以while的平均时间为O(1),所以

    总体时间就只是for的时间,O(n))。

    高度中找左边和右边第一个比他小的位置,然后就是此高度对应的宽度。

 1  public int largestRectangleArea(int[] height) {
 2      if(height == null || height.length == 0) return 0;
 3      Stack<Integer> s = new Stack<Integer>();
 4      int max = 0;
 5      for(int i = 0; i <= height.length; i++) {
 6          int currHeight = (i == height.length)?-1:height[i];
 7          while(!s.isEmpty() && currHeight <= height[s.peek()]) {
 8              int h = height[s.pop()];
 9              int w = s.isEmpty()? i: i - s.peek() - 1;
10              max = Math.max(max, h*w);
11          }
12          s.push(i);
13      }
14      return max;
15  }
View Code

 

4 哈希表原理(增删查的复杂度O(1),二叉查找树logn)

Cache (一个大的哈希表):memory级别的访问, ns级别,500M/b
数据库:文件系统访问,硬盘,微秒级别,500k/b

 1 public void hashFunc(String key) {
 2       //hash本身就是杂乱无章的表示。所以不要去理解表达的含义,大概类似于把key按33进制表示出来,同时让他最后的值处于HASH_TABLE_SIZE的范围中。
 3       int sum = 0;
 4       for(int i = 0; i < key.length(); i++ ) {
 5           sum = sum * 33 + (int)key.charAt(i);
 6           sum = sum % HASH_TABLE_SIZE;  //如果不包含这一步,则相当于把key当成33进制数表示出来。   1234 按十进制表达: ((1*10 + 2)*10+3)*10 + 4;      
 7                                         //HASH_TABLE_SIZE 表示开辟的数组大小,实际存储的数据size/HASH_TABLE_SIZE = 1/10 最好,否则size再大,
 8                                         //产生冲突的概率会增大。每一次操作都保证sum在HASH_TABLE_SIZE的范围内。
 9     
10       }
11       return sum;
12   }    
View Code

5 重哈希(需要把所有的数重新计算插入一遍,很麻烦,所以尽量避免重哈希的出现,开始定义hash大小时数组开的空间大点。)

http://www.lintcode.com/zh-cn/problem/rehashing/

注意点: 增加链表时,一定要new,而且是· .next = new ListNode,不然赋值不过来。不知道地址传递到底是怎么传的。

 1  public ListNode[] rehashing(ListNode[] hashTable) {
 2         if(hashTable == null || hashTable.length == 0) return hashTable;
 3         ListNode[] newHash = new ListNode[hashTable.length * 2];
 4         int len = newHash.length;
 5         for(int i = 0; i < hashTable.length; i++) {
 6             ListNode node = hashTable[i];
 7             int index = 0;
 8             while(node != null ) {
 9                  index = (node.val%len + len) % len;
10                  if(newHash[index] == null) {
11                      newHash[index] = new ListNode(node.val);
12                      node = node.next;
13                      continue;
14                  } 
15                  ListNode head = newHash[index];
16                  while( head.next != null) {
17                      head = head.next;
18                  }
19                 head = new ListNode(node.val);
20           
21                 node = node.next;
22             }
23         }
24         return newHash;
25     }
View Code

 6 快乐数(hash)

http://www.lintcode.com/zh-cn/problem/happy-number/

注意点: 注意按位取元素的方法

 1 private int getNextHappy(int n) {
 2         int sum = 0;
 3         while (n != 0) {
 4             sum += (n % 10) * (n % 10);
 5             n /= 10;
 6         }
 7         return sum;
 8     }
 9     
10     public boolean isHappy(int n) {
11         HashSet<Integer> hash = new HashSet<Integer>();
12         while (n != 1) {
13             if (hash.contains(n)) {
14                 return false;
15             }
16             hash.add(n);
17             n = getNextHappy(n);
18         }
19         return true;
20     }
View Code

 7 LRU缓存策略

http://www.lintcode.com/zh-cn/problem/lru-cache/

注意点: node结点写在主类里面,因为它只需要在此类里暴露,不需要对外显示。

     一共有两种存储的数据结构,map存放指定容量的key,value数据,LinkedList存放各种数据的前后放入关系。所以操作数据时,要同时维护这两种数据结构,get方法只需要维护链表,set方法两个都需要维护。

(堆相关)

 8 数据流中位数    优先队列/heap :O(log N) Add    O(log N) Remove   O(1) Min/Max    二叉树实现的,根节点是最值,每次移除根节点,都需要从剩下的结点中找到最值

          再移到根上,所以remove是O(logn)。堆排序只能保证根是最大(最小),不能保证整体是按照顺序来排序的。

http://www.lintcode.com/zh-cn/problem/data-stream-median/ 

注意点: offer  poll方法

    maxHeap里存放小于等于中位数的数字,minHeap里放大于中位数的数字。 中位数,则 maxHeap.size() == minHeap.size() 或者maxHeap.size() == minHeap.size()+1

 1  public int[] medianII(int[] nums) {
 2         // write your code here  
 3     if(nums == null || nums.length == 0) return null;
 4     PriorityQueue<Integer> minHeap = new PriorityQueue<Integer>();
 5     PriorityQueue<Integer> maxHeap = new PriorityQueue<Integer>(1, new Comparator<Integer>(){
 6         //@Override   可以不写,但是compare方法参数必须是Integer,不能是int
 7         public int compare(Integer x, Integer y) {
 8             return y - x;
 9         }
10     });
11     int[] res = new int[nums.length];
12     res[0] = nums[0];
13     maxHeap.offer(nums[0]);
14     for(int i = 1; i < nums.length; i++) {
15         if(nums[i] <= maxHeap.peek()) {
16             maxHeap.offer(nums[i]);
17         } else {
18             minHeap.offer(nums[i]);
19         }
20         
21         //开始进入两个元素时,size上,maxHeap = minHeap 或者 maxHeap = minHeap +2,经过下面的if语句,转变成maxHeap = minHeap 
22         // 每一轮进来后,只会出现maxHeap = minHeap 或者maxHeap = minHeap +1两种情况。(类似一种递推的关系)
23         if(maxHeap.size() > minHeap.size() + 1) {
24             minHeap.offer(maxHeap.poll());
25         } else if( maxHeap.size() < minHeap.size()) {
26             maxHeap.offer(minHeap.poll());
27         } 
28         res[i] = maxHeap.peek();
29     }
30     return res;    
31 }
View Code

 9 堆化  (有点堆排序的意思)

http://www.lintcode.com/zh-cn/problem/heapify/

注意点:    0         1          2      3      4      5     6      原序列

    1   2      3       4       5      6            原序列元素对应的子树角标。

    A[0]肯定是最小值。

     siftdown的O(n)遍历方式很独特,从中间开始遍历。

 1 //   0 1 2 3 4 5 6 7  len = 8,   mid = 3     对于位置i,两个子树2i+1,2i+2;对于位置i-1,子树2(i-1) +1, 2(i-1) +2,即2i-1和2i。
 2                                              //也就是说 i-1,i-1恰好能连续覆盖掉2i-1,2i,2i+1,2i+2;
 3  //   0 1 2 3 4 5 6 7 8  len = 9, mid = 4
 4  
 5     public void heapify(int[] A) {
 6         // write your code here
 7         //O(n)完成,只遍历一次,但是遍历的方式不是简单的从头到尾,而是从中间往左。
 8         int mid = (A.length - 1)/2;
 9         for(int i = mid; i >=0; i--) {
10             siftdown(A, i);
11         }
12         
13     }
14     
15     private void siftdown(int[] A, int k) {
16         int son = 0;
17         while(2*k+1 < A.length) {   //从后往前保证 两个子树比根小,即有一定顺序。如果靠前的位置发生过swap,那也要保证swap之后,后面的位置还是有序
18                                     //所以有k = son
19             son = 2*k+1;
20             if(2*k+2 < A.length && A[2*k+2] <= A[son] ) son = 2*k+2; //son是两个子树中的较小的一个
21             
22             if(A[son] < A[k]) {
23                 swap(A, son, k);
24                 k = son;
25             } else {
26                 break;
27             }
28         }
29         
30     }
31     private void swap(int[] A, int x, int y) {
32         int temp = A[x];
33         A[x] = A[y];
34         A[y] = temp;
35     }
View Code

 10 丑数

http://www.lintcode.com/zh-cn/problem/ugly-number/

http://www.lintcode.com/zh-cn/problem/ugly-number-ii/#

注意点: 不理解丑数2的话看代码里的解释。

 1  public int nthUglyNumber(int n) {
 2      int[] uglyArr = new int[n];
 3      uglyArr[0] = 1;
 4      //p2,p3,p5代表三个指针,指向uglyArr数组的索引。
 5      int p2 = 0, p3=0, p5 = 0;
 6      for(int i= 1; i < n; i++) {
 7          //  <= 说明此索引位置的丑数已经乘以过2了,即已有的丑数数组中已经包含由此位置丑数*2所对应的丑数了,
 8          //  那么下一轮再乘的时候,就不能用此位置的丑数*2了,要用下一个丑数来乘。
 9          //  所以p2表示:当前待乘以2来候选作为下一个丑数的数的角标
10          //为啥不是用uglyArr[i - 1]来乘2呢,比如1, 2,,3 用 3 *2 显然比 2* 2大,所以下一个丑数不是3*2。
11          //所以应该记录的是之前的丑数,1,2,3是否乘过2,3,5,p2= 1,p3= 1, p5 = 0表示5还没有乘过角标0的数,2没有乘过角标1的数,3没有乘过角标1的数。
12          if(uglyArr[p2] * 2 <= uglyArr[i - 1]) p2++;
13          if(uglyArr[p3] * 3 <= uglyArr[i - 1]) p3++;
14          if(uglyArr[p5] * 5 <= uglyArr[i - 1]) p5++;
15          
16          //这一轮最小值是乘的2,3还是5会在下一轮通过if判断出来,判断出来后,p2,p3,p5中有且只有一个指针会移动1个位置。
17          uglyArr[i] = Math.min(uglyArr[p2] * 2, 
18                         Math.min(uglyArr[p3] * 3, uglyArr[p5] * 5));
19      }
20      return uglyArr[n - 1];
21  }
View Code

 11.字符串查找

http://www.lintcode.com/zh-cn/problem/strstr/

注意点: O(n)实现 Rabin-Karp算法

  1234  : 234=10(123-100)+4 = 123*10+4-1000 此处用的是后面的计算方式

  (a+b)%b= (a%b+b%b)%b= a%b  这正是当hashcode<0时采取的做法,也就是对它取模,hashcode%HASH_SIZE=(hashcode+HASH_SIZE)%HASH_SIZE

 1 /** 验证下面的结论是否普遍成立:
 2      *     1%11*10%11*10%11=100%11=1  power
 3      *     5%11*10%11*10%11= 5    =1 * 5 
 4      *  结论是:成立
 5      */
 6     public static void main(String[] args) {
 7         int HASH_SIZE=1000000;
 8         for(int numberSize = 2; numberSize < 10; numberSize++) {
 9             int power = 1;
10             for(int i = 0; i <4; i++) {
11                 power = (power*31)%HASH_SIZE;
12             }
13             for(int i =1; i < 10; i++) {
14                 int count = 0;
15                 int num = i;
16                 int count0 = (num* power)%HASH_SIZE;
17                 for(int j = 0; j < 5; j++) {
18                     if(j != 0) num = 0;
19                     count = (count*31+num)%HASH_SIZE;
20                 }
21                 if(count != count0){
22                     System.out.println(i);
23                     break;
24                 }
25             }
26             System.out.println(numberSize+"::finish");
27         }
28     }
验证
 1 private int HASH_SIZE = 1000000;
 2 
 3     public int strStr(String source, String target) {
 4         // Write your code here
 5         if (source == null || target == null) {
 6             return -1;
 7         }
 8         int m = source.length();
 9         int n = target.length();
10         if (n == 0) {
11             return 0;
12         }
13         if (m == 0) {
14             return -1;
15         }
16         int targetCode = 0;
17         for (int i = 0; i < n; i++) {
18             targetCode = (targetCode * 31 + target.charAt(i)) % HASH_SIZE;
19         }
20         int power = 1;
21         for (int i = 0; i < n; i++) {
22             power = (power * 31) % HASH_SIZE;
23         }
24         int hashCode = 0;
25         for (int i = 0; i < m; i++) {
26             //只有一开始i = n-1 时hashCode记录的是n个数的hash值,
27             //之后一直记录的是n+1个数的值,所以power才要乘31^n 而不是31^(n-1)
28             hashCode = (hashCode * 31 + source.charAt(i)) % HASH_SIZE;
29             if (i < n - 1) {
30                 continue;
31             }
32             if (i >= n) {
33                 hashCode = hashCode - (source.charAt(i - n) * power)% HASH_SIZE ;
34                 //为啥可能出现hashcode<0? 因为新添加的一位导致hashcode的值>HASH_SIZE,出现了取模的情况,
35                 // 而 a%b = (a+b)%b,所以<0的情况,原本的hashcode计算方式应该是:
36                 // hashcode = hashCode + HASH_SIZE - (source.charAt(i - n) * power)% HASH_SIZE ;
37                 // 所以如果遇到<0的情况,加HASH_SIZE就好了。
38                 if (hashCode < 0) {
39                     hashCode += HASH_SIZE;
40                 }
41             }
42             // 0~n-1  i=n-1, 0 = i - n+1
43             // 1~n    i=n,   1 = i - n+1
44             if (hashCode == targetCode) {
45                 if (source.substring(i - n + 1, i + 1).equals(target)) {
46                     return i - n + 1;
47                 }
48 
49             }
50         }
51         return -1;
52     }
View Code

 

 

graph and search

1 克隆图

http://www.lintcode.com/zh-cn/problem/clone-graph/#

拓扑排序

http://www.lintcode.com/zh-cn/problem/topological-sorting/#

注意点:图肯定要用hashMap

    遍历完图的方式:while(start < res.size()) { start++}   res动态增长,size变化,所有结点都加入进去后,就不变了,而start也增长,实现遍历完全的目的。

 1 public UndirectedGraphNode cloneGraph(UndirectedGraphNode node) {
 2         //图的BFS,类似二叉树的BFS,不过需要统计邻居关系,避免已经访问过的邻居重复访问,所以用Map+ Queue实现。
 3         //Queue可以用ArrayList + 头索引的位置来表示
 4         if(node == null) return node;
 5         ArrayList<UndirectedGraphNode> list = new ArrayList();  //放原先的结点
 6         Map<UndirectedGraphNode,UndirectedGraphNode> map = new HashMap();  //放复制节点和原先结点的映射关系
 7         int start = 0;
 8         
 9         list.add(node);
10         map.put(node, new UndirectedGraphNode(node.label));
11         while(start < list.size()) {
12             UndirectedGraphNode curr = list.get(start++);
13             for(int i = 0; i < curr.neighbors.size(); i++) {
14                 if(!map.containsKey(curr.neighbors.get(i))) {
15                     list.add(curr.neighbors.get(i));
16                     map.put(curr.neighbors.get(i), new UndirectedGraphNode(curr.neighbors.get(i).label));
17                 }
18             }
19         }
20         
21         // copy edge
22         for(int i = 0; i < list.size(); i++) {
23             UndirectedGraphNode curr = list.get(i);
24             for(int j = 0; j < curr.neighbors.size(); j++) {
25                 map.get(curr).neighbors.add(map.get(curr.neighbors.get(j)));
26             }
27         }
28         return map.get(node);
29     }
View Code

 2 全排列(DFS)

http://www.lintcode.com/zh-cn/problem/permutations/

http://www.lintcode.com/zh-cn/problem/subsets/   子集

http://www.lintcode.com/zh-cn/problem/subsets-ii/#

http://www.lintcode.com/zh-cn/problem/permutations-ii/#

http://www.lintcode.com/zh-cn/problem/combination-sum/#     list里add一个元素,再做dfs,然后再remove掉

注意点: 写递归,想清楚两件事:

            1.递归是做了一件什么样的事情,和参数的关系是什么

            2.想清楚递归在什么时候return

            3.想清楚递归关系,把大问题化解成小问题解决。

错误点:  返回  List<List<Integer>>,则声明为:List<List<Integer>> rst = new ArrayList<List<Integer>>();    List<Integer> list = new ArrayList<Integer>();

    返回ArrayList<ArrayList<Integer>>,  声明为:ArrayList<ArrayList<Integer>> rst = new ArrayList<ArrayList<Integer>>();

                         ArrayList<Integer> list = new ArrayList<Integer>();   按上面的声明无法通过编译

 1 public List<List<Integer>> permute(int[] nums) {
 2     // write your code here
 3     if(nums == null) return null;
 4     List<List<Integer>> rst = new ArrayList<List<Integer>>();
 5     ArrayList<Integer> list = new ArrayList<Integer>();
 6     if(nums.length == 0) {
 7         rst.add(list);
 8         return rst;
 9     }
10     helper(rst, list, nums );
11     return rst;
12 }
13 
14 public void helper(List<List<Integer>> rst, ArrayList<Integer> list, int[] nums){
15     if(list.size() == nums.length) {
16         //不能rst.add(list) 地址传递,最后内容都没了
17         rst.add(new ArrayList<Integer>(list));
18         return;
19     }
20     for(int i = 0; i < nums.length; i++) {    //假设nums={1,2,3,4},最外的循环进来,for4次对应四种情况:     [ ]
21                                               //                                                                |--[1]
22                                               //                                                                |--[2]
23                                               //                                                                |--[3]
24                                               //                                                                |--[4]
25                                               //对于每一种情况,比如[1],又分为了三种  [1]
26                                               //                                         |--[2]
27                                               //                                         |--[3]
28                                               //                                         |--[4]
29                                               //......最后直到list.size()==nums.length,所有元素都放进去了,才作为一次结果返回。
30         
31         if(list.contains(nums[i])) {
32             continue;
33         }
34         list.add(nums[i]);
35         helper(rst, list, nums);
36         list.remove(list.size() - 1);
37     }
38 }
View Code

3 N皇后问题

http://www.lintcode.com/zh-cn/problem/n-queens/#

注意点:分成4块,每块函数各司其职

错误点:     (cols.get(i) == j)?sb.append('Q'):sb.append('.'); (错)     sb.append(j == cols.get(i) ? 'Q' : '.');(对)  三目表达式,一个整体

 1  ArrayList<ArrayList<String>> solveNQueens(int n) {
 2     if(n <= 0) return null;
 3     ArrayList<ArrayList<String>> rst = new ArrayList<ArrayList<String>>();
 4     search(rst, new ArrayList<Integer>(), n);
 5     return rst;
 6         
 7  }
 8 
 9  private void search(ArrayList<ArrayList<String>> rst, ArrayList<Integer> cols, int n) {
10      if(cols.size() == n) {
11          rst.add(drawChess(cols));
12          return;
13      }
14      for(int i = 0; i < n; i++) {
15          if(!isValid(cols, i)) {
16             continue; 
17          }
18          cols.add(i);
19          search(rst, cols, n);
20          cols.remove(cols.size() - 1);
21      }
22  }
23  //查看第cols.size()行的第colIndex 列是否合法
24  //根据cols元素的放法的定义,不可能出现同一行,只可能有同一列或者同一斜行的情况。
25  private boolean isValid(ArrayList<Integer> cols, int colIndex) {
26      int rowIndex = cols.size();
27      for(int i = 0; i < rowIndex; i++) {
28          if(cols.get(i) == colIndex) return false;
29          // right-top  to left-down
30         // 。Q 。 。
31         // 。。 Q  。   左上到右下情况下的相同斜线:  (0, 1)  (1,2)  行序号-列序号的值相等。
32         
33         // 。。 。 Q
34         // 。。 Q  。   右上到左下情况下的相同斜线:  (0, 3)  (1,2)  行序号+列序号的值相等。
35          if(cols.get(i) + i == rowIndex + colIndex) return false;
36          if(cols.get(i) - i == colIndex - rowIndex ) return false;
37      }
38      return true;
39  }
40  private ArrayList<String> drawChess(ArrayList<Integer> cols) {
41      ArrayList<String> list = new ArrayList<String>();
42      for(int i = 0; i < cols.size(); i++) {
43          StringBuilder sb = new StringBuilder();
44         for(int j = 0; j < cols.size(); j++) {
45             //(cols.get(i) == j)?sb.append('Q'):sb.append('.');
46             sb.append(j == cols.get(i) ? 'Q' : '.');
47         }
48         list.add(sb.toString());
49      }
50      return list;
51  }
View Code

4 单词接龙

http://www.lintcode.com/zh-cn/problem/word-ladder/      BFS   找最短路

http://www.lintcode.com/zh-cn/problem/word-ladder-ii/#    找所有方案,需要DFS,同时也要找最短路对应的所有方案,所以是DFS+BFS

注意点: BFS,因为每次只变一步,可以画出一张单词变化图出来, lot-log-pog  

    第一种方法超时了,差别主要在找下一个合法单词的方式上,一种是遍历dict,依次判断每个单词是否是合法的单词,另一种是先写出当前单词的所有的合法

    改变单词来,然后判断它是否在dict中。结果是第二种方式更优,为啥??

  1  public int ladderLength(String start, String end, Set<String> dict) {
  2     // 超时了,dict很大的时候,isValidChange 用时过长。
  3     if(start == null || end == null || dict == null) return 0;
  4     if(isValidChange(start,end)) return 2;
  5     List<String> list = new ArrayList<String>();
  6     list.add(start);
  7     return searchValidChange(list, dict, end);
  8 }
  9 private int searchValidChange(List<String> list, Set<String> dict,String end) {
 10     int level = 1;
 11     int pos = 0;
 12     while(list.size() < dict.size() + 1) {
 13         int len = list.size();
 14         while(pos < len) {
 15             for(String s1 : dict) {
 16                 if(list.contains(s1)) continue;
 17                 if(isValidChange(list.get(pos), s1)) {
 18                     if(isValidChange(s1, end)) return level+2;
 19                     list.add(s1);
 20                 }
 21             }
 22             pos++;
 23         }
 24         level++;
 25     }
 26     return 0;
 27 }
 28 private boolean isValidChange(String s1, String s2) {
 29     if(s1.length() != s2.length()) return false;
 30     int count = 0;
 31     for(int i = 0; i < s1.length(); i++) {
 32     if(s1.charAt(i) == s2.charAt(i)) continue;
 33         count++;    
 34         //if(count > 1) return false;
 35     }
 36     return count == 1;
 37 }
 38 //----------------------------------------------------
 39  public int ladderLength(String start, String end, Set<String> dict) {
 40         if (dict == null) {
 41             return 0;
 42         }
 43 
 44         if (start.equals(end)) {
 45             return 1;
 46         }
 47         
 48         dict.add(start);
 49         dict.add(end);
 50 
 51         HashSet<String> hash = new HashSet<String>();
 52         Queue<String> queue = new LinkedList<String>();
 53         queue.offer(start);
 54         hash.add(start);
 55         
 56         int length = 1;
 57         while(!queue.isEmpty()) {
 58             length++;
 59             int size = queue.size();
 60             for (int i = 0; i < size; i++) {
 61                 String word = queue.poll();
 62                 for (String nextWord: getNextWords(word, dict)) {
 63                     if (hash.contains(nextWord)) {
 64                         continue;
 65                     }
 66                     if (nextWord.equals(end)) {
 67                         return length;
 68                     }
 69                     
 70                     hash.add(nextWord);
 71                     queue.offer(nextWord);
 72                 }
 73             }
 74         }
 75         return 0;
 76     }
 77 
 78     // replace character of a string at given index to a given character
 79     // return a new string
 80     private String replace(String s, int index, char c) {
 81         char[] chars = s.toCharArray();
 82         chars[index] = c;
 83         return new String(chars);
 84     }
 85     
 86     // get connections with given word.
 87     // for example, given word = 'hot', dict = {'hot', 'hit', 'hog'}
 88     // it will return ['hit', 'hog']
 89     private ArrayList<String> getNextWords(String word, Set<String> dict) {
 90         ArrayList<String> nextWords = new ArrayList<String>();
 91         for (char c = 'a'; c <= 'z'; c++) {
 92             for (int i = 0; i < word.length(); i++) {
 93                 if (c == word.charAt(i)) {
 94                     continue;
 95                 }
 96                 String nextWord = replace(word, i, c);
 97                 if (dict.contains(nextWord)) {
 98                     nextWords.add(nextWord);
 99                 }
100             }
101         }
102         return nextWords;
103     }
View Code

 

 1 //懒得看了,bfs写的就问题很大。用一个队列就能解决的问题,套了半天map,死循环,还绕。
 2 private Map<String, Integer> map;
 3 private int minLen = Integer.MAX_VALUE;
 4 private List<List<String>> rsts;
 5 private Set<String> dict;
 6 public List<List<String>> findLadders(String start, String end, Set<String> dict) {
 7     // write your code here  
 8     if(start == null || end == null) return null;
 9     rsts = new ArrayList<>();
10     List<String> rst = new ArrayList<String>();
11     rst.add(start);
12     if(start.equals(end)) {
13         rsts.add(new ArrayList<String>(rst));
14         return rsts;
15     }
16     if(dict == null) return null;
17     map = findShortestLen(dict, end);
18     this.dict = dict;
19     dict.add(end);
20     //dict.add(start);
21     dfs(rst, start, end);
22     return rsts;
23 }
24 //dfs
25 private void dfs(List<String> rst,String start, String end) {
26     if(map.get(start) != null && map.get(start) == 2 && rst.size() + 1 == minLen) {
27         List<String> addRst = new ArrayList<String>(rst);
28         addRst.add(end);
29         rsts.add(addRst);
30     }
31     List<String> list = findNextWords(dict, start);
32     for(String s : list) {
33         //List<String> addList = new ArrayList<String>();
34         if(!map.containsKey(s)) continue;
35         if(minLen < rst.size() + map.get(s)) continue;
36         else {
37             minLen = rst.size() + map.get(s);    
38             rst.add(s);
39             dfs(rst, s, end );
40             rst.remove(rst.size() - 1);    
41         }
42         
43     }
44     return;
45 }
46 //bfs    
47 private Map<String, Integer> findShortestLen(Set<String> dict, String end) {
48     Map<String, Integer> map = new HashMap<>();
49     map.put(end, 1);
50     int len = 1;
51     while(map.size() < dict.size()) {  ///zzz, abc, abd,   zzz永远也放不进map,死循环,先不管。    
52         Map<String, Integer> temp = new HashMap<>();
53         for(String s1 : map.keySet()) {
54             if(map.get(s1) != len) continue;
55             List<String> list = findNextWords(dict, s1);
56             if(list == null) continue;
57             for(String s2 : list) {
58                 if(map.containsKey(s2) || temp.containsKey(s2)) continue;
59                 temp.put(s2, len + 1);
60             }
61         }
62         len++;
63         map.putAll(temp);
64     }
65     return map;
66 }
67 private List<String> findNextWords(Set<String> dict, String end) {
68     List<String> list = new ArrayList<String>();
69     for(int i = 'a'; i <= 'z'; i++) {
70         for(int j = 0; j < end.length(); j++) {
71             if(i == end.charAt(j)) continue;
72             String s = replaceOneChar(end, j, (char)i);
73             if(dict.contains(s)) list.add(s);
74         }
75     }
76     return list;
77 }
78 private String replaceOneChar(String end, int pos, char c) {
79     char[] chars = end.toCharArray();
80     chars[pos] = c;
81     return Arrays.toString(chars);
82 }
接龙2_Me_wrong

 

 1 public List<List<String>> findLadders(String start, String end, Set<String> dict) {
 2     List<List<String>> rsts = new ArrayList<>();
 3     List<String> rst = new ArrayList<String>();
 4     Map<String,List<String>> map = new HashMap(); 
 5     Map<String, Integer> distance = new HashMap();
 6     dict.add(start);
 7     dict.add(end); //避免dict中有无start和end造成的分类讨论
 8     bfs(map, distance, start , end, dict);
 9     dfs(rsts,map, distance,rst, end, start);
10     return rsts;
11 }
12 //从end开始添加
13 private void dfs(List<List<String>> rsts, Map<String,List<String>> map, Map<String, Integer> distance, List<String> rst, String curr,
14                  String start) {
15     rst.add(curr);
16     if(curr.equals(start)) {
17         Collections.reverse(rst);
18         rsts.add(new ArrayList(rst));
19         Collections.reverse(rst);
20         return;
21     }
22 /*    不要这样取元素
23     List<String> nexts = findNexts(dict, curr);
24     for(String next : nexts) {
25         if(distance.get(next) +1 == distance.get(curr)) {
26             dfs(rsts,map, distance, rst, next, start, dict);
27         }
28     }*/
29        /* 这样只能取出一种结果来
30         List<String> list = map.get(curr);
31         dfs(rsts,map, distance, rst, list.get(list.size() - 1) , start, dict);*/
32         List<String> list = map.get(curr);
33         for(String s : list) {
34             if(distance.get(s) +1 == distance.get(curr)) {
35                 dfs(rsts,map, distance, rst, s , start);
36             }
37         }
38     rst.remove(rst.size() - 1);
39     
40 }
41 //计算每一个字符串到start的路径距离 
42 private void bfs(Map<String,List<String>> map, Map<String, Integer> distance, String start, String end, Set<String> dict) {
43     Queue<String> q = new LinkedList();
44     q.offer(start);
45     distance.put(start, 0);
46     for(String s : dict) {
47         map.put(s, new ArrayList());
48     }
49     while(!q.isEmpty()) {
50         String curr = q.poll();
51         List<String> nexts = findNexts(dict, curr);
52         for(String next : nexts) {
53         /*    这样只能取出一种接过来
54             if(distance.containsKey(next)) continue;
55             distance.put(next, distance.get(curr) + 1);
56             map.get(next).add(curr);
57             q.offer(next);*/
58             map.get(next).add(curr);
59             if(!distance.containsKey(next)) {
60                 distance.put(next, distance.get(curr) + 1);
61                 q.offer(next);
62             }
63         }
64     }
65 }
66 private List<String> findNexts(Set<String> dict, String curr) {
67     List<String> nexts = new ArrayList();
68     for(char ch = 'a'; ch <='z'; ch++) {
69         for(int i = 0; i < curr.length(); i++) {
70             if (ch == curr.charAt(i)) continue;
71             String s = curr.substring(0, i) + ch + curr.substring(i+1);
72             if(dict.contains(s)) {
73                 nexts.add(s);
74             }
75         }    
76     }
77     return nexts;
78 }
还是wrong,不知道哪里有错