平方求幂。

int ipow(int base, int exp)
{
    int result = 1;
    for (;;)
    {
        if (exp & 1)
            result *= base;
        exp >>= 1;
        if (!exp)
            break;
        base *= base;
    }

    return result;
}

这是在非对称密码学中对大数进行模求幂的标准方法。

请注意，平方求幂并不是最优的方法。这可能是一种适用于所有指数值的通用方法，但对于特定的指数值，可能有更好的序列，需要更少的乘法。

例如，如果你想计算x^15，用平方求幂的方法会给你:

x^15 = (x^7)*(x^7)*x 
x^7 = (x^3)*(x^3)*x 
x^3 = x*x*x

这一共有6次乘法。

事实证明，这可以通过“仅仅”5次加法链幂运算来完成。

n*n = n^2
n^2*n = n^3
n^3*n^3 = n^6
n^6*n^6 = n^12
n^12*n^3 = n^15

没有有效的算法来找到这个最优的乘法序列。从维基百科:

The problem of finding the shortest addition chain cannot be solved by dynamic programming, because it does not satisfy the assumption of optimal substructure. That is, it is not sufficient to decompose the power into smaller powers, each of which is computed minimally, since the addition chains for the smaller powers may be related (to share computations). For example, in the shortest addition chain for a¹⁵ above, the subproblem for a⁶ must be computed as (a³)² since a³ is re-used (as opposed to, say, a⁶ = a²(a²)², which also requires three multiplies).

除了Elias的答案，当使用有符号整数实现时，会导致未定义行为，当使用无符号整数实现时，会导致高输入的不正确值，

下面是平方求幂的修改版本，它也适用于有符号整数类型，并且不会给出错误的值:

#include <stdint.h>

#define SQRT_INT64_MAX (INT64_C(0xB504F333))

int64_t alx_pow_s64 (int64_t base, uint8_t exp)
{
    int_fast64_t    base_;
    int_fast64_t    result;

    base_   = base;

    if (base_ == 1)
        return  1;
    if (!exp)
        return  1;
    if (!base_)
        return  0;

    result  = 1;
    if (exp & 1)
        result *= base_;
    exp >>= 1;
    while (exp) {
        if (base_ > SQRT_INT64_MAX)
            return  0;
        base_ *= base_;
        if (exp & 1)
            result *= base_;
        exp >>= 1;
    }

    return  result;
}

使用该函数的注意事项:

(1 ** N) == 1
(N ** 0) == 1
(0 ** 0) == 1
(0 ** N) == 0

如果将发生任何溢出或换行，则返回0;

I used int64_t, but any width (signed or unsigned) can be used with little modification. However, if you need to use a non-fixed-width integer type, you will need to change SQRT_INT64_MAX by (int)sqrt(INT_MAX) (in the case of using int) or something similar, which should be optimized, but it is uglier, and not a C constant expression. Also casting the result of sqrt() to an int is not very good because of floating point precission in case of a perfect square, but as I don't know of any implementation where INT_MAX -or the maximum of any type- is a perfect square, you can live with that.

更一般的解决方案考虑负指数

private static int pow(int base, int exponent) {

    int result = 1;
    if (exponent == 0)
        return result; // base case;

    if (exponent < 0)
        return 1 / pow(base, -exponent);
    int temp = pow(base, exponent / 2);
    if (exponent % 2 == 0)
        return temp * temp;
    else
        return (base * temp * temp);
}

一种非常特殊的情况是，当你需要2^(-x ^ y)时，其中x当然是负的y太大了，不能对int型进行移位。你仍然可以用浮点数在常数时间内完成2^x。

struct IeeeFloat
{

    unsigned int base : 23;
    unsigned int exponent : 8;
    unsigned int signBit : 1;
};


union IeeeFloatUnion
{
    IeeeFloat brokenOut;
    float f;
};

inline float twoToThe(char exponent)
{
    // notice how the range checking is already done on the exponent var 
    static IeeeFloatUnion u;
    u.f = 2.0;
    // Change the exponent part of the float
    u.brokenOut.exponent += (exponent - 1);
    return (u.f);
}

使用double作为基底类型，可以得到更多的2的幂。 (非常感谢评论者帮助整理这篇文章)。

还有一种可能性是，学习更多关于IEEE浮点数的知识，其他幂运算的特殊情况可能会出现。

下面是Java中的方法

private int ipow(int base, int exp)
{
    int result = 1;
    while (exp != 0)
    {
        if ((exp & 1) == 1)
            result *= base;
        exp >>= 1;
        base *= base;
    }

    return result;
}