I thought about this: Is there a performance difference in these two practices:

1. Store the return value of a function in a temporary variable than give that variable as a parameter to another function.
2. Put the function into the other function.

Specification

Assuming all classes and functions are written correctly.

Case 1.

ClassA a = function1();
ClassB b = function2(a);
function3(b);

Case 2.

function3(function2(function1()));

I know there aren't a big difference with only one run, but supposed that we could run this a lot of times in a loop, I created some tests.

Test

#include <iostream>
#include <ctime>
#include <math.h>
using namespace std;

int main()
{
   clock_t start = clock();
   clock_t ends = clock();

   // Case 1.
   start = clock();
   for (int i=0; i<10000000; i++)
   {
      double a = cos(1);
      double b = pow(a, 2);
      sqrt(b);
   }
   ends = clock();
   cout << (double) (ends - start) / CLOCKS_PER_SEC << endl;

   // Case 2.
   start = clock();
   for (int i=0; i<10000000; i++)
      sqrt(pow(cos(1),2));
   ends = clock();
   cout << (double) (ends - start) / CLOCKS_PER_SEC << endl;
   return 0;
}

Results

• Case 1 = 6.375
• Case 2 = 0.031

Why is the first one is much slower, and if the second one is faster why dont we always write code that way? Anyway does the second pratice has a name?
I also wondered what happens if I create the variables outside the for loop in the first case, but the result was the same. Why?

Break the throw-this-all-away optimization if you want the computational crunch and your numbers become much more consistent. Ensuring the code to get the proper value is actually run and not entirely thrown out, I've assigned the results in both tests to a volatile local (which isn't exactly proper usage of volatile, but does a decent job of ensuring only the value-creation is the significant delta).

#include <iostream>
#include <ctime>
#include <cmath>
using namespace std;

int main()
{
    clock_t start;
    volatile double val;

    for (int j=1;j<=10;j++)
    {
        // Case 1.
        start = clock();
        for (int i=0; i<2000000; i++)
        {
            double a = cos(1);
            double b = pow(a, 2);
            val = sqrt(b);
        }
        cout << j << ':' << (double) (clock() - start) / CLOCKS_PER_SEC << endl;

        // Case 2.
        start = clock();
        for (int i=0; i<2000000; i++)
            val = sqrt(pow(cos(1),2));
        cout << j << ':' << (double) (clock() - start) / CLOCKS_PER_SEC << endl << endl;
    }
    return 0;
}

Produces the following release-compiled output on my Macbook Air (which is no speed demon by any stretch):

1:0.001465
1:0.001305

2:0.001292
2:0.001424

3:0.001297
3:0.001351

4:0.001366
4:0.001342

5:0.001196
5:0.001376

6:0.001341
6:0.001303

7:0.001396
7:0.001422

8:0.001429
8:0.001427

9:0.001408
9:0.001398

10:0.001317
10:0.001353

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