显然，如果你是在为下一个阅读你的代码的人写代码，那么你应该追求“x/2”的清晰度。

然而，如果速度是你的目标，那就两种方法都试一试，把握好时间。几个月前，我做了一个位图卷积例程，它涉及到在一个整数数组中步进，并将每个元素除以2。我做了各种各样的事情来优化它，包括用“x>>1”代替“x/2”的老技巧。

当我计算这两种方式时，我惊奇地发现x/2比x>>1快

这是使用Microsoft VS2008 c++并打开默认优化。

x / 2更清晰，x >> 1快不了多少(根据一个微基准测试，对于Java JVM快30%左右)。正如其他人所注意到的，对于负数，舍入略有不同，所以当您想处理负数时必须考虑这一点。一些编译器可能会自动将x / 2转换为x >> 1，如果他们知道这个数字不可能是负数(即使我无法验证这一点)。

即使x / 2可能不使用(慢)除法CPU指令，因为一些捷径是可能的，但它仍然比x >> 1慢。

(This is a C / C++ question, other programming languages have more operators. For Java there is also the unsigned right shift, x >>> 1, which is again different. It allows to correctly calculate the mean (average) value of two values, so that (a + b) >>> 1 will return the mean value even for very large values of a and b. This is required for example for binary search if the array indices can get very large. There was a bug in many versions of binary search, because they used (a + b) / 2 to calculate the average. This doesn't work correctly. The correct solution is to use (a + b) >>> 1 instead.)

X = X / 2;是合适的代码使用..但是一个操作取决于你自己的程序，你想要产生怎样的输出。

使用最能描述您要做的事情的操作。

如果你将数字作为一个比特序列来处理，请使用bitshift。 如果你把它当作一个数值，使用除法。

请注意，它们并不完全相等。对于负整数，它们可以给出不同的结果。例如:

-5 / 2  = -2
-5 >> 1 = -3

(ideone)

显然，如果你是在为下一个阅读你的代码的人写代码，那么你应该追求“x/2”的清晰度。

然而，如果速度是你的目标，那就两种方法都试一试，把握好时间。几个月前，我做了一个位图卷积例程，它涉及到在一个整数数组中步进，并将每个元素除以2。我做了各种各样的事情来优化它，包括用“x>>1”代替“x/2”的老技巧。

当我计算这两种方式时，我惊奇地发现x/2比x>>1快

这是使用Microsoft VS2008 c++并打开默认优化。

我想说有几件事需要考虑。

Bitshift should be faster, as no special computation is really needed to shift the bits, however as pointed out, there are potential issues with negative numbers. If you are ensured to have positive numbers, and are looking for speed then I would recommend bitshift. The division operator is very easy for humans to read. So if you are looking for code readability, you could use this. Note that the field of compiler optimization has come a long way, so making code easy to read and understand is good practice. Depending on the underlying hardware, operations may have different speeds. Amdal's law is to make the common case fast. So you may have hardware that can perform different operations faster than others. For example, multiplying by 0.5 may be faster than dividing by 2. (Granted you may need to take the floor of the multiplication if you wish to enforce integer division).

如果您追求的是纯粹的性能，我建议您创建一些可以执行数百万次操作的测试。对执行进行多次采样(您的样本量)，以确定哪一个在统计上最适合您的操作系统/硬件/编译器/代码。