2.5链表 链式A+B

aaarticlea/png;base64,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" alt="" />

把测试代码也写上。

 #include <iostream>
 #include <vector>
 #include <string>
 #include <queue>
 #include <algorithm>
 using namespace std;

 struct ListNode
 {
     int val;
     struct ListNode *next;
     ListNode(int x):val(x), next(NULL) {}
 };

 ListNode* create(vector<int> v)
 {
     ListNode *p = new ListNode();
     ListNode *temp1 = p;
     for (int i = ;i < v.size();i++)
     {
         ListNode *temp2 = new ListNode(v[i]);
         temp1->next = temp2;
         temp1 = temp1->next;
     }
     return p->next;
 }

 void printList(ListNode* result)
 {
     queue<int> que;
     ListNode* temp = result;
     while (temp)
     {
         que.push(temp->val);
         temp = temp->next;
     }
     while (!que.empty())
     {
         cout << que.front();
         que.pop();
     }
 }

 class Plus {
 public:
     int cal(int a, int b, int &flag)
     {
         int sum = a + b + flag;
         if (sum > )
         {
             flag = ;
             return sum % ;
         }
         else
         {
             flag = ;
             return sum;
         }
     }

     ListNode* plusAB(ListNode* a, ListNode* b)
     {
         queue<int> qua, qub;
         while (a)
         {
             qua.push(a->val);
             a = a->next;
         }
         while (b)
         {
             qub.push(b->val);
             b = b->next;
         }
         while (qua.size() < qub.size())
         {
             qua.push();
         }
         while (qua.size() > qub.size())
         {
             qub.push();
         }

         ListNode* pHead = new ListNode();
         ListNode* pM = pHead;

         int flag = ;
         while (!qua.empty())
         {
             int ans = cal(qua.front(), qub.front(), flag);
             ListNode* temp = new ListNode(ans);
             pM->next = temp;
             pM = pM->next;
             qua.pop();
             qub.pop();
         }
         if (flag)
         {
             ListNode* temp = new ListNode();
             pM->next = temp;
             pM = pM->next;
         }
         return pHead->next;
     }
 };

 int main()
 {
     vector<int> v1{ ,, };
     vector<int> v2{ ,, };
     ListNode* p1 = create(v1);
     ListNode* p2 = create(v2);
     ListNode* ret;
     Plus solution;
     ret=solution.plusAB(p1, p2);
     printList(ret);
     return ;
 }