Move computation from run time to compile time

Reason

To decrease code size and run time. To avoid data races by using constants. To catch errors at compile time (and thus eliminate the need for error-handling code).

Example

double square(double d) { return d*d; }
static double s2 = square(2);    // old-style: dynamic initialization

constexpr double ntimes(double d, int n)   // assume 0 <= n
{
        double m = 1;
        while (n--) m *= d;
        return m;
}
constexpr double s3 {ntimes(2, 3)};  // modern-style: compile-time initialization

Code like the initialization of s2 isn't uncommon, especially for initialization that's a bit more complicated than square(). However, compared to the initialization of s3 there are two problems:

• we suffer the overhead of a function call at run time
• s2 just might be accessed by another thread before the initialization happens.

Note: you can't have a data race on a constant.

Example

Consider a popular technique for providing a handle for storing small objects in the handle itself and larger ones on the heap.

constexpr int on_stack_max = 20;

template<typename T>
struct Scoped {     // store a T in Scoped
        // ...
    T obj;
};

template<typename T>
struct On_heap {    // store a T on the free store
        // ...
        T* objp;
};

template<typename T>
using Handle = typename std::conditional<(sizeof(T) <= on_stack_max),
                    Scoped<T>,      // first alternative
                    On_heap<T>      // second alternative
               >::type;

void f()
{
    Handle<double> v1;                   // the double goes on the stack
    Handle<std::array<double, 200>> v2;  // the array goes on the free store
    // ...
}

Assume that Scoped and On_heap provide compatible user interfaces. Here we compute the optimal type to use at compile time. There are similar techniques for selecting the optimal function to call.

Note

The ideal is not to try to execute everything at compile time. Obviously, most computations depend on inputs, so they can't be moved to compile time, but beyond that logical constraint is the fact that complex compile-time computation can seriously increase compile times and complicate debugging. It is even possible to slow down code by compile-time computation. This is admittedly rare, but by factoring out a general computation into separate optimal sub-calculations, it is possible to render the instruction cache less effective.

Enforcement

• Look for simple functions that might be constexpr (but are not).
• Look for functions called with all constant-expression arguments.
• Look for macros that could be constexpr.