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顺序表的基本运算代码实例
2017-12-27 13:53:32         来源:qq_37151962的博客  
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顺序表的基本运算代码实例

#include    
#include   
using namespace std;  
typedef int kong;  
typedef struct  
{  
     int data[50];  
     int length;  
}sqlist;  
void Createlist(sqlist*&L,kong a[],int n);//建立一个空的线性表  
void DispList(sqlist *L);//顺序输出线性表的内容。  
int ListEmpty(sqlist *L);//判断线性表是否为空;  
int main()  
{  
     sqlist *sq;  
     kong b[5]={1,2,3,4,5};  
     Createlist(sq,b,5);  
     DispList(sq);  
     return 0;  
}  
void Createlist(sqlist*&L,kong a[],int n)  
{  
     int x;  
     L=(sqlist *)malloc(sizeof(sqlist));  
     for(x=0;xdata[x]=a[x];  
          L->length=n;  
}  
void DispList(sqlist *L)  
{  
     int x;  
     if(ListEmpty(L)==1)  
          return;  
     for(x=0;xlength;x++)  
          cout<data[x];  
     cout<length==0);  
}  
<p>运行结果:</p><p>
<img src="data:image/png;base64,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" alt="">
</p><p>知识点总结:</p><p>实现顺序表基本运算,运用了viod和int函数,又用指针和链表。</p>  
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