小老虎007 发表于 2021-4-15 23:35:07

关于scanf()函数参数问题

本帖最后由 小老虎007 于 2021-4-15 23:37 编辑

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



int main()
{
      
int v1;
int v2;
int var = {0};

scanf("%s", var, v1, v2);

printf("%s", var);      

return 0;
}

输入超过var的长度值,v1,v2被写入。
这V1,V2跟在后面竟然也能通过编译,不知道为什么,求解释!!



yuxijian2020 发表于 2021-4-16 08:36:46

scanf本身就是不定长参数,你写多少参数都行,但是只会根据第一个字符串内的占位符来接受用户输入
顺便说一句,scanf 是需要取址符的....

小老虎007 发表于 2021-4-17 13:39:56

yuxijian2020 发表于 2021-4-16 08:36
scanf本身就是不定长参数,你写多少参数都行,但是只会根据第一个字符串内的占位符来接受用户输入
顺便说 ...

数组名,也可表示地址

1055741510 发表于 2021-4-21 00:21:30

你这么写编译器会给警告的 var表示的是整型地址 前面占位符怎么能用%s?
页: [1]
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