下面是一个计算x ** y的O(1)算法，灵感来自这条评论。它适用于32位有符号int。

对于较小的y值，它使用平方求幂。对于较大的y值，只有少数x值的结果不会溢出。这个实现使用一个查找表来读取结果而不进行计算。

对于溢出，C标准允许任何行为，包括崩溃。但是，我决定对LUT索引进行边界检查，以防止内存访问违反，这可能是令人惊讶和不受欢迎的。

伪代码:

If `x` is between -2 and 2, use special-case formulas.
Otherwise, if `y` is between 0 and 8, use special-case formulas.
Otherwise:
    Set x = abs(x); remember if x was negative
    If x <= 10 and y <= 19:
        Load precomputed result from a lookup table
    Otherwise:
        Set result to 0 (overflow)
    If x was negative and y is odd, negate the result

C代码:

#define POW9(x) x * x * x * x * x * x * x * x * x
#define POW10(x) POW9(x) * x
#define POW11(x) POW10(x) * x
#define POW12(x) POW11(x) * x
#define POW13(x) POW12(x) * x
#define POW14(x) POW13(x) * x
#define POW15(x) POW14(x) * x
#define POW16(x) POW15(x) * x
#define POW17(x) POW16(x) * x
#define POW18(x) POW17(x) * x
#define POW19(x) POW18(x) * x

int mypow(int x, unsigned y)
{
    static int table[8][11] = {
        {POW9(3), POW10(3), POW11(3), POW12(3), POW13(3), POW14(3), POW15(3), POW16(3), POW17(3), POW18(3), POW19(3)},
        {POW9(4), POW10(4), POW11(4), POW12(4), POW13(4), POW14(4), POW15(4), 0, 0, 0, 0},
        {POW9(5), POW10(5), POW11(5), POW12(5), POW13(5), 0, 0, 0, 0, 0, 0},
        {POW9(6), POW10(6), POW11(6), 0, 0, 0, 0, 0, 0, 0, 0},
        {POW9(7), POW10(7), POW11(7), 0, 0, 0, 0, 0, 0, 0, 0},
        {POW9(8), POW10(8), 0, 0, 0, 0, 0, 0, 0, 0, 0},
        {POW9(9), 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
        {POW9(10), 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}
    };

    int is_neg;
    int r;

    switch (x)
    {
    case 0:
        return y == 0 ? 1 : 0;
    case 1:
        return 1;
    case -1:
        return y % 2 == 0 ? 1 : -1;
    case 2:
        return 1 << y;
    case -2:
        return (y % 2 == 0 ? 1 : -1) << y;
    default:
        switch (y)
        {
        case 0:
            return 1;
        case 1:
            return x;
        case 2:
            return x * x;
        case 3:
            return x * x * x;
        case 4:
            r = x * x;
            return r * r;
        case 5:
            r = x * x;
            return r * r * x;
        case 6:
            r = x * x;
            return r * r * r;
        case 7:
            r = x * x;
            return r * r * r * x;
        case 8:
            r = x * x;
            r = r * r;
            return r * r;
        default:
            is_neg = x < 0;
            if (is_neg)
                x = -x;
            if (x <= 10 && y <= 19)
                r = table[x - 3][y - 9];
            else
                r = 0;
            if (is_neg && y % 2 == 1)
                r = -r;
            return r;
        }
    }
}

这是对平方求幂效率的后续讨论。

这种方法的优点是它在log(n)时间内运行。例如，如果你要计算一个巨大的数，比如x^1048575(2^20 - 1)，你只需要循环20次，而不是使用朴素方法的100万+次。

此外，在代码复杂性方面，它比试图找到最优的乘法序列更简单，这是la Pramod的建议。

编辑:

我想我应该在有人指责我可能会溢出之前澄清一下。这种方法假设您有某种巨大的int库。

如果您在编译时知道指数(并且它是一个整数)，您可以使用模板展开循环。这可以更有效，但我想在这里演示基本原则:

#include <iostream>

template<unsigned long N>
unsigned long inline exp_unroll(unsigned base) {
    return base * exp_unroll<N-1>(base);
}

我们使用模板特化来终止递归:

template<>
unsigned long inline exp_unroll<1>(unsigned base) {
    return base;
}

指数需要在运行时已知，

int main(int argc, char * argv[]) {
    std::cout << argv[1] <<"**5= " << exp_unroll<5>(atoi(argv[1])) << ;std::endl;
}

如果要取2的a次方。最快的方法是按幂位移位。

2 ** 3 == 1 << 3 == 8
2 ** 30 == 1 << 30 == 1073741824 (A Gigabyte)

O(log N)的解决方案在Swift…

// Time complexity is O(log N)
func power(_ base: Int, _ exp: Int) -> Int { 

    // 1. If the exponent is 1 then return the number (e.g a^1 == a)
    //Time complexity O(1)
    if exp == 1 { 
        return base
    }

    // 2. Calculate the value of the number raised to half of the exponent. This will be used to calculate the final answer by squaring the result (e.g a^2n == (a^n)^2 == a^n * a^n). The idea is that we can do half the amount of work by obtaining a^n and multiplying the result by itself to get a^2n
    //Time complexity O(log N)
    let tempVal = power(base, exp/2) 

    // 3. If the exponent was odd then decompose the result in such a way that it allows you to divide the exponent in two (e.g. a^(2n+1) == a^1 * a^2n == a^1 * a^n * a^n). If the eponent is even then the result must be the base raised to half the exponent squared (e.g. a^2n == a^n * a^n = (a^n)^2).
    //Time complexity O(1)
    return (exp % 2 == 1 ? base : 1) * tempVal * tempVal 

}

我已经实现了记忆所有计算权力的算法，然后在需要时使用它们。比如x^13等于(x^2)^2^2 * x^2 * x其中x^2^2是从表中取出来的而不是再计算一次。这基本上是@Pramod answer的实现(但在c#中)。 需要的乘法数是Ceil(Log n)

public static int Power(int base, int exp)
{
    int tab[] = new int[exp + 1];
    tab[0] = 1;
    tab[1] = base;
    return Power(base, exp, tab);
}

public static int Power(int base, int exp, int tab[])
    {
         if(exp == 0) return 1;
         if(exp == 1) return base;
         int i = 1;
         while(i < exp/2)
         {  
            if(tab[2 * i] <= 0)
                tab[2 * i] = tab[i] * tab[i];
            i = i << 1;
          }
    if(exp <=  i)
        return tab[i];
     else return tab[i] * Power(base, exp - i, tab);
}