C++ code segments

本文介绍了C++中的一些基本概念和技术,包括函数别名调用、类型转换、数组定义、指针操作以及字符和字符串处理等内容。通过具体示例展示了如何在C++程序中使用这些特性。

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一.function alias invocation(引用)

#include <iostream>
using namespace std;
void aliasFun(int &, int &);
int main()
{
int num = 10;
cout << "Num = " << num << endl;
int &i = num;
i = 20;
cout << "i = " << i << endl;
cout << "Num = " << num << endl;
int x = 200;
int y = 300;
aliasFun(x,y);
cout << "x = " << x << ", " << "y = " << y << endl;
return 0;
}
void aliasFun(int &a,int &b)
{
a = 4;
b = 10;
}

--------------------------------------------
二.type cast
#include <iostream>
using namespace std;
int main(int argc, char **argv)
{
double d = 3.1415926;
int i1 = static_cast<int>(d);
int i2 = (int)d; // old method
cout << "i1 = " << i1 << endl;
cout << "i2 = " << i2 << endl;
return 0;
}

-----------------------------------------

3.Array definition

int a[4]; // definition
int a[4] = {1,10,2,4} // defination and initialization

------------------------------------------

4.pointer
int a = 10;
int *p = &a;
int *p = new int;
int *p = new int[10]; //dynamic allocate array
delete p;
delete [] p;

void swap(int *num1,int *num2)
{
int temp = *num1;
*num1 = *num2;
*num2 = temp;
}

int main(){
int x = 10;
int y = 20;
swap(&x,&y);
}

-------------------------------

5.character && string
char *p = "hello very good";
while(p != "\0")
{
cout << *p++;
}

------------
char str[10] = "hello!";
char *p = str;
for(int i=0;i<6;i++)
{
cout << *(p+i);
}
### C++ Segment Cover Algorithm Implementation In addressing the segment cover problem within C++, one approach involves defining structures or classes that represent intervals (segments). The core of this issue revolves around determining whether a set of given segments can fully cover another specified interval. A common method employs sorting and greedy algorithms. A simplified version might look like: ```cpp #include <iostream> #include <vector> #include <algorithm> using namespace std; struct Interval { int start; int end; }; bool compareInterval(Interval i1, Interval i2) { return i1.start < i2.start || (i1.start == i2.start && i1.end > i2.end); } int findMinSegmentsToCover(vector<Interval>& intervals, int targetStart, int targetEnd) { sort(intervals.begin(), intervals.end(), compareInterval); vector<int> dp(targetEnd + 1, INT_MAX); // Minimum number of segments needed to reach each point up to targetEnd. dp[targetStart] = 0; // No cost at starting position. for (auto& interval : intervals) { if (interval.start >= targetStart && interval.end <= targetEnd) { for (int j = interval.start; j <= min(interval.end, targetEnd); ++j) { if (dp[interval.start] != INT_MAX) { // Only update when previous positions are reachable. dp[j] = min(dp[j], dp[interval.start] + 1); } } } } return dp[targetEnd] == INT_MAX ? -1 : dp[targetEnd]; } ``` This code snippet defines an `Interval` structure along with a function named `findMinSegmentsToCover`, which calculates the minimum amount of provided segments required to completely cover from `targetStart` to `targetEnd`. If no such combination exists, `-1` will be returned as indicated by the logic inside the program[^1]. For practical applications involving large datasets or specific requirements regarding performance optimization techniques including memory management strategies could come into play. For instance, choosing between heap-based allocations versus stack-based ones depending upon size constraints and access patterns may influence overall efficiency significantly[^3]. However, these considerations go beyond basic implementations focusing purely on solving the segment covering challenge itself.
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