如果您有一个比您想要测试的数据类型大的数据类型(比如您做了一个32位的添加，而您有一个64位的类型)，那么这将检测是否发生溢出。我的例子是一个8位的添加。但它可以放大。

uint8_t x, y;    /* Give these values */
const uint16_t data16    = x + y;
const bool carry        = (data16 > 0xFF);
const bool overflow     = ((~(x ^ y)) & (x ^ data16) & 0x80);

它基于本页解释的概念:http://www.cs.umd.edu/class/spring2003/cmsc311/Notes/Comb/overflow.html

对于一个32位的例子，0xFF变成0xFFFFFFFF, 0x80变成0x80000000，最后uint16_t变成uint64_t。

注意:这捕获整数加法/减法溢出，我意识到你的问题涉及乘法。在这种情况下，分裂可能是最好的办法。这通常是calloc实现确保参数在相乘以获得最终大小时不会溢出的一种方式。

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)

一种简单的方法是重写所有操作符(特别是+和*)，并在执行操作之前检查是否有溢出。

最简单的方法是将unsigned long转换为unsigned long，进行乘法运算，并将结果与0x100000000LL进行比较。

你可能会发现这比你在例子中做除法更有效。

哦，它在C和c++中都可以工作(因为你已经用这两种语言标记了问题)。

我在看glibc手册。这里提到了整数溢出陷阱(FPE_INTOVF_TRAP)作为SIGFPE的一部分。这将是理想的，除了手册中令人讨厌的部分:

FPE_INTOVF_TRAP 整数溢出(在C程序中不可能，除非您以特定于硬件的方式启用溢出捕获)。

真的有点遗憾。

为了扩展Head Geek的答案，有一种更快的方法来执行addition_is_safe;

bool addition_is_safe(unsigned int a, unsigned int b)
{
    unsigned int L_Mask = std::numeric_limits<unsigned int>::max();
    L_Mask >>= 1;
    L_Mask = ~L_Mask;

    a &= L_Mask;
    b &= L_Mask;

    return ( a == 0 || b == 0 );
}

这使用了机器架构安全，64位和32位无符号整数仍然可以正常工作。基本上，我创建了一个掩码，它将屏蔽除最重要的位外的所有内容。然后，对两个整数进行掩码，如果其中任何一个没有设置该位，则加法是安全的。

如果在某个构造函数中预初始化掩码，这将更快，因为它永远不会改变。

#include <stdio.h>
#include <stdlib.h>

#define MAX 100 

int mltovf(int a, int b)
{
    if (a && b) return abs(a) > MAX/abs(b);
    else return 0;
}

main()
{
    int a, b;

    for (a = 0; a <= MAX; a++)
        for (b = 0; b < MAX; b++) {

        if (mltovf(a, b) != (a*b > MAX)) 
            printf("Bad calculation: a: %d b: %d\n", a, b);

    }
}