ccf的题目
本帖最后由 白牡丹秀色可餐 于 2022-4-24 22:23 编辑第一块代码是我写的,第二块代码是网上找到的(测试是一百分),但不清楚为什么我的代码一直只有九十分,请问是有什么漏洞吗?(题目在下面)
#include<stdio.h>
#define N 100000
int main()
{
int a;
int n,k;
int b,c;
int count = 0;
a = 1;
scanf("%d %d", &n,&k);
while (k--) {
scanf("%d %d", &b, &c);
if (a != 1) {
count++;
}
a = 1;
}
printf("%d", count);
return 0;
}
#include <iostream>
#include <cstring>
#include <algorithm>
#include <cmath>
using namespace std;
const int N = 100010;
bool a; //记录该变量是否已经初始化
int n, k;
int main()
{
cin >> n >> k;
a = 1; //a为常量,不需要初始化
int res = 0;
while (k --)
{
int x, y;
cin >> x >> y;
if (!a) res ++; //右值未初始化,则答案加一
a = 1; //另左值标记为已初始化
}
cout << res;
return 0;
}
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
最后发现是没有初始化数组a
if (a == 0) 傻眼貓咪 发表于 2022-4-24 20:11
if (a == 0)
我试了还是一样,最后好像啊没有初始化数组a 白牡丹秀色可餐 发表于 2022-4-24 22:22
我试了还是一样,最后好像啊没有初始化数组a
好吧
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