题目

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解决代码及点评


/*
功能:设链表中每个结点包括学号、成绩、和指针三个字段, 试编程序将大于平均成绩的各个结点打印出来。 */ #include<stdio.h>
#include<stdlib.h> #define N 10 //10名同学 struct student //创建链表
{
int ID;
int course;
struct student *pNext;
}; typedef struct student STU; STU *init(int id, int cur) //设置头结点
{
STU *p = (STU *)malloc(sizeof(STU));
if (p == NULL)return NULL;
p->ID = id;
p->course = cur;
p->pNext = NULL;
return p;
} void insert(STU *pHead, int id, int cur) //插入结点
{
STU *pNode = (STU *)malloc(sizeof(STU));
if (pNode == NULL)exit;
pHead->pNext = pNode;
pNode->ID = id;
pNode->course = cur;
pNode->pNext = NULL;
} int count(STU *pHead); //求和
void showAll(STU *pHead);
double getAverage(STU *pHead,int n); void main()
{
STU *pHead = init(NULL,NULL); //头结点没有内容,next指向第一个学生
int i = 1; //学号
STU *p = pHead; //当前结点位置
while (i <= N) //总共创建10个结点,每个结点代表一个学生
{
insert(p, i, rand() % 40 + 60); //插入一个学生信息
i++;
p = p->pNext; //当前指针后移
} showAll(pHead); //输出链表信息,所有学生信息 double ave = getAverage(pHead,N); //获得平均分数
printf("\nAverage = %f\n",ave); STU *pa = pHead->pNext;
while (pa != NULL)
{
if (pa->course > ave) // 打印分数大于平均分的学生科目信息
{
printf("ID: %d,\tachi = %d\n",pa->ID,pa->course);
}
pa = pa->pNext;
}
system("pause");
} double getAverage(STU *pHead, int n) // 计算平均分
{
return count(pHead)/(double)n;
} void showAll(STU *pHead) // 打印所有学生信息
{
STU *pa = pHead->pNext;
while (pa != NULL) //输出链表信息
{
printf("%d:\t%d\n", pa->ID, pa->course);
pa = pa->pNext;
} }
int count(STU *pHead) // 计算成绩之和
{
STU *pa = pHead->pNext;
int sum = 0;
while (pa != NULL)
{
sum += pa->course;
pa = pa->pNext;
}
return sum;
}

代码编译以及运行

由于资源上传太多,资源频道经常被锁定无法上传资源,同学们可以打开VS2013自己创建工程,步骤如下:

1)新建工程

2)选择工程

3)创建完工程如下图:

4)增加文件,右键点击项目

5)在弹出菜单里做以下选择

6)添加文件

7)拷贝代码与运行

程序运行结果

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" alt="" />




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