我看到你用的是无符号整数。根据定义，在C中(我不了解c++)，无符号算术不会溢出…所以，至少对C来说，你的观点是没有意义的:)

对于有符号整数，一旦出现溢出，就会发生未定义行为(UB)，程序可以做任何事情(例如:使测试不确定)。

#include <limits.h>

int a = <something>;
int x = <something>;
a += x;              /* UB */
if (a < 0) {         /* Unreliable test */
  /* ... */
}

要创建一个符合要求的程序，您需要在生成溢出之前测试溢出。该方法也可以用于无符号整数:

// For addition
#include <limits.h>

int a = <something>;
int x = <something>;
if (x > 0 && a > INT_MAX - x) // `a + x` would overflow
if (x < 0 && a < INT_MIN - x) // `a + x` would underflow

// For subtraction
#include <limits.h>
int a = <something>;
int x = <something>;
if (x < 0 && a > INT_MAX + x) // `a - x` would overflow
if (x > 0 && a < INT_MIN + x) // `a - x` would underflow

// For multiplication
#include <limits.h>

int a = <something>;
int x = <something>;
// There may be a need to check for -1 for two's complement machines.
// If one number is -1 and another is INT_MIN, multiplying them we get abs(INT_MIN) which is 1 higher than INT_MAX
if (a == -1 && x == INT_MIN) // `a * x` can overflow
if (x == -1 && a == INT_MIN) // `a * x` (or `a / x`) can overflow
// general case
if (x != 0 && a > INT_MAX / x) // `a * x` would overflow
if (x != 0 && a < INT_MIN / x) // `a * x` would underflow

对于除法(INT_MIN和-1特殊情况除外)，不可能超过INT_MIN或INT_MAX。

内联程序集允许您直接检查溢出位。如果你打算使用c++，你真的应该学习汇编。

有一种方法可以确定一个操作是否可能溢出，使用操作数中最高位的位置和一些基本的二进制数学知识。

对于加法，任何两个操作数的结果(最多)比最大操作数的最高1位多1位。例如:

bool addition_is_safe(uint32_t a, uint32_t b) {
    size_t a_bits=highestOneBitPosition(a), b_bits=highestOneBitPosition(b);
    return (a_bits<32 && b_bits<32);
}

对于乘法，任何两个操作数的结果(最多)是操作数的位数之和。例如:

bool multiplication_is_safe(uint32_t a, uint32_t b) {
    size_t a_bits=highestOneBitPosition(a), b_bits=highestOneBitPosition(b);
    return (a_bits+b_bits<=32);
}

类似地，你可以像这样估计a的b次方结果的最大大小:

bool exponentiation_is_safe(uint32_t a, uint32_t b) {
    size_t a_bits=highestOneBitPosition(a);
    return (a_bits*b<=32);
}

(当然，用比特数代替目标整数。)

我不确定确定数字中最高的1位位置的最快方法，这里有一个蛮力方法:

size_t highestOneBitPosition(uint32_t a) {
    size_t bits=0;
    while (a!=0) {
        ++bits;
        a>>=1;
    };
    return bits;
}

它不是完美的，但它能让你在做运算之前知道是否有两个数会溢出。我不知道它是否会比您建议的方式检查结果更快，因为highestOneBitPosition函数中的循环，但它可能会(特别是如果您事先知道操作数中有多少位)。

用double计算结果。它们有15位有效数字。您的要求在c上有一个硬上限108 -它最多可以有8位数字。因此，如果它在范围内，结果将是精确的，否则它将不会溢出。

这里有一个非常快速的方法来检测溢出，至少是加法，这可能会为乘法、除法和乘方提供线索。

其思想是，正是因为处理器会让值归零，而C/ c++是从任何特定的处理器抽象出来的，你可以:

uint32_t x, y;
uint32_t value = x + y;
bool overflow = value < (x | y);

这既确保了如果一个操作数为零，另一个操作数为零，则不会错误地检测到溢出，而且比前面建议的许多NOT/XOR/ and /test操作要快得多。

正如所指出的，这种方法虽然比其他更精细的方法更好，但仍然是可优化的。以下是包含优化的原始代码的修订:

uint32_t x, y;
uint32_t value = x + y;
const bool overflow = value < x; // Alternatively "value < y" should also work

一种更有效、更廉价的检测乘法溢出的方法是:

uint32_t x, y;
const uint32_t a = (x >> 16U) * (y & 0xFFFFU);
const uint32_t b = (x & 0xFFFFU) * (y >> 16U);
const bool overflow = ((x >> 16U) * (y >> 16U)) +
    (a >> 16U) + (b >> 16U);
uint32_t value = overflow ? UINT32_MAX : x * y;

这将导致UINT32_MAX溢出，或乘法的结果。在这种情况下，允许对有符号整数进行乘法运算是严格未定义的行为。

值得注意的是，这使用部分Karatsuba方法乘法分解来计算64位乘法的高32位，以检查是否应该设置它们中的任何一个，以了解32位乘法是否溢出。

如果使用c++，你可以把这个转换成一个简洁的小lambda来计算溢出，这样检测器的内部工作就被隐藏了:

uint32_t x, y;
const bool overflow
{
    [](const uint32_t x, const uint32_t y) noexcept -> bool
    {
        const uint32_t a{(x >> 16U) * uint16_t(y)};
        const uint32_t b{uint16_t(x) * (y >> 16U)};
        return ((x >> 16U) * (y >> 16U)) + (a >> 16U) + (b >> 16U);
    }(x, y)
};
uint32_t value{overflow ? UINT32_MAX : x * y};

I see that a lot of people answered the question about overflow, but I wanted to address his original problem. He said the problem was to find ab=c such that all digits are used without repeating. Ok, that's not what he asked in this post, but I'm still think that it was necessary to study the upper bound of the problem and conclude that he would never need to calculate or detect an overflow (note: I'm not proficient in math so I did this step by step, but the end result was so simple that this might have a simple formula).

重点是问题要求的a b c的上限是98.765.432。不管怎样，先把问题分成琐碎部分和非琐碎部分:

X0 == 1(9、8、7、6、5、4、3、2的所有排列都是解) X1 == x(无解) 0b == 0(不可能解) 1b == 1(无解) Ab, a > 1, b > 1(非平凡)

Now we just need to show that no other solution is possible and only the permutations are valid (and then the code to print them is trivial). We go back to the upper bound. Actually the upper bound is c ≤ 98.765.432. It's the upper bound because it's the largest number with 8 digits (10 digits total minus 1 for each a and b). This upper bound is only for c because the bounds for a and b must be much lower because of the exponential growth, as we can calculate, varying b from 2 to the upper bound:

    9938.08^2 == 98765432
    462.241^3 == 98765432
    99.6899^4 == 98765432
    39.7119^5 == 98765432
    21.4998^6 == 98765432
    13.8703^7 == 98765432
    9.98448^8 == 98765432
    7.73196^9 == 98765432
    6.30174^10 == 98765432
    5.33068^11 == 98765432
    4.63679^12 == 98765432
    4.12069^13 == 98765432
    3.72429^14 == 98765432
    3.41172^15 == 98765432
    3.15982^16 == 98765432
    2.95305^17 == 98765432
    2.78064^18 == 98765432
    2.63493^19 == 98765432
    2.51033^20 == 98765432
    2.40268^21 == 98765432
    2.30883^22 == 98765432
    2.22634^23 == 98765432
    2.15332^24 == 98765432
    2.08826^25 == 98765432
    2.02995^26 == 98765432
    1.97741^27 == 98765432

注意，例如最后一行:它说1.97^27 ~98M。因此，例如，1^27 == 1和2^27 == 134.217.728，这不是一个解决方案，因为它有9位数字(2 > 1.97，所以它实际上比应该测试的要大)。可以看到，用于测试a和b的组合非常小。对于b == 14，我们需要尝试2和3。对于b == 3，我们从2开始，到462结束。结果均小于~98M。

现在只需测试以上所有的组合，找出不重复任何数字的组合:

    ['0', '2', '4', '5', '6', '7', '8'] 84^2 = 7056
    ['1', '2', '3', '4', '5', '8', '9'] 59^2 = 3481
    ['0', '1', '2', '3', '4', '5', '8', '9'] 59^2 = 3481 (+leading zero)
    ['1', '2', '3', '5', '8'] 8^3 = 512
    ['0', '1', '2', '3', '5', '8'] 8^3 = 512 (+leading zero)
    ['1', '2', '4', '6'] 4^2 = 16
    ['0', '1', '2', '4', '6'] 4^2 = 16 (+leading zero)
    ['1', '2', '4', '6'] 2^4 = 16
    ['0', '1', '2', '4', '6'] 2^4 = 16 (+leading zero)
    ['1', '2', '8', '9'] 9^2 = 81
    ['0', '1', '2', '8', '9'] 9^2 = 81 (+leading zero)
    ['1', '3', '4', '8'] 3^4 = 81
    ['0', '1', '3', '4', '8'] 3^4 = 81 (+leading zero)
    ['2', '3', '6', '7', '9'] 3^6 = 729
    ['0', '2', '3', '6', '7', '9'] 3^6 = 729 (+leading zero)
    ['2', '3', '8'] 2^3 = 8
    ['0', '2', '3', '8'] 2^3 = 8 (+leading zero)
    ['2', '3', '9'] 3^2 = 9
    ['0', '2', '3', '9'] 3^2 = 9 (+leading zero)
    ['2', '4', '6', '8'] 8^2 = 64
    ['0', '2', '4', '6', '8'] 8^2 = 64 (+leading zero)
    ['2', '4', '7', '9'] 7^2 = 49
    ['0', '2', '4', '7', '9'] 7^2 = 49 (+leading zero)

没有一个匹配问题(这也可以通过缺少'0'，'1'，…“9”)。

下面是解决该问题的示例代码。还要注意，这是用Python编写的，不是因为它需要任意精确整数(代码不会计算任何大于9800万的数字)，而是因为我们发现测试的数量非常少，所以我们应该使用高级语言来利用其内置的容器和库(还要注意:代码有28行)。

    import math

    m = 98765432
    l = []
    for i in xrange(2, 98765432):
        inv = 1.0/i
        r = m**inv
        if (r < 2.0): break
        top = int(math.floor(r))
        assert(top <= m)

        for j in xrange(2, top+1):
            s = str(i) + str(j) + str(j**i)
            l.append((sorted(s), i, j, j**i))
            assert(j**i <= m)

    l.sort()
    for s, i, j, ji in l:
        assert(ji <= m)
        ss = sorted(set(s))
        if s == ss:
            print '%s %d^%d = %d' % (s, i, j, ji)

        # Try with non significant zero somewhere
        s = ['0'] + s
        ss = sorted(set(s))
        if s == ss:
            print '%s %d^%d = %d (+leading zero)' % (s, i, j, ji)