从http://www.quora.com/What-is-the-difference-between-compiled-and-interpreted-programming-languages

There is no difference, because “compiled programming language” and “interpreted programming language” aren’t meaningful concepts. Any programming language, and I really mean any, can be interpreted or compiled. Thus, interpretation and compilation are implementation techniques, not attributes of languages. Interpretation is a technique whereby another program, the interpreter, performs operations on behalf of the program being interpreted in order to run it. If you can imagine reading a program and doing what it says to do step-by-step, say on a piece of scratch paper, that’s just what an interpreter does as well. A common reason to interpret a program is that interpreters are relatively easy to write. Another reason is that an interpreter can monitor what a program tries to do as it runs, to enforce a policy, say, for security. Compilation is a technique whereby a program written in one language (the “source language”) is translated into a program in another language (the “object language”), which hopefully means the same thing as the original program. While doing the translation, it is common for the compiler to also try to transform the program in ways that will make the object program faster (without changing its meaning!). A common reason to compile a program is that there’s some good way to run programs in the object language quickly and without the overhead of interpreting the source language along the way. You may have guessed, based on the above definitions, that these two implementation techniques are not mutually exclusive, and may even be complementary. Traditionally, the object language of a compiler was machine code or something similar, which refers to any number of programming languages understood by particular computer CPUs. The machine code would then run “on the metal” (though one might see, if one looks closely enough, that the “metal” works a lot like an interpreter). Today, however, it’s very common to use a compiler to generate object code that is meant to be interpreted—for example, this is how Java used to (and sometimes still does) work. There are compilers that translate other languages to JavaScript, which is then often run in a web browser, which might interpret the JavaScript, or compile it a virtual machine or native code. We also have interpreters for machine code, which can be used to emulate one kind of hardware on another. Or, one might use a compiler to generate object code that is then the source code for another compiler, which might even compile code in memory just in time for it to run, which in turn . . . you get the idea. There are many ways to combine these concepts.

编译器和解释器做同样的工作:将一种编程语言翻译成另一种编程语言，通常更接近硬件，通常是直接可执行的机器代码。

Traditionally, "compiled" means that this translation happens all in one go, is done by a developer, and the resulting executable is distributed to users. Pure example: C++. Compilation usually takes pretty long and tries to do lots of expensive optmization so that the resulting executable runs faster. End users don't have the tools and knowledge to compile stuff themselves, and the executable often has to run on a variety of hardware, so you can't do many hardware-specific optimizations. During development, the separate compilation step means a longer feedback cycle.

Traditionally, "interpreted" means that the translation happens "on the fly", when the user wants to run the program. Pure example: vanilla PHP. A naive interpreter has to parse and translate every piece of code every time it runs, which makes it very slow. It can't do complex, costly optimizations because they'd take longer than the time saved in execution. But it can fully use the capabilities of the hardware it runs on. The lack of a separrate compilation step reduces feedback time during development.

But nowadays "compiled vs. interpreted" is not a black-or-white issue, there are shades in between. Naive, simple interpreters are pretty much extinct. Many languages use a two-step process where the high-level code is translated to a platform-independant bytecode (which is much faster to interpret). Then you have "just in time compilers" which compile code at most once per program run, sometimes cache results, and even intelligently decide to interpret code that's run rarely, and do powerful optimizations for code that runs a lot. During development, debuggers are capable of switching code inside a running program even for traditionally compiled languages.

极端和简单的情况:

A compiler will produce a binary executable in the target machine's native executable format. This binary file contains all required resources except for system libraries; it's ready to run with no further preparation and processing and it runs like lightning because the code is the native code for the CPU on the target machine. An interpreter will present the user with a prompt in a loop where he can enter statements or code, and upon hitting RUN or the equivalent the interpreter will examine, scan, parse and interpretatively execute each line until the program runs to a stopping point or an error. Because each line is treated on its own and the interpreter doesn't "learn" anything from having seen the line before, the effort of converting human-readable language to machine instructions is incurred every time for every line, so it's dog slow. On the bright side, the user can inspect and otherwise interact with his program in all kinds of ways: Changing variables, changing code, running in trace or debug modes... whatever.

说完了这些，让我来解释一下，生活不再那么简单了。例如,

Many interpreters will pre-compile the code they're given so the translation step doesn't have to be repeated again and again. Some compilers compile not to CPU-specific machine instructions but to bytecode, a kind of artificial machine code for a ficticious machine. This makes the compiled program a bit more portable, but requires a bytecode interpreter on every target system. The bytecode interpreters (I'm looking at Java here) recently tend to re-compile the bytecode they get for the CPU of the target section just before execution (called JIT). To save time, this is often only done for code that runs often (hotspots). Some systems that look and act like interpreters (Clojure, for instance) compile any code they get, immediately, but allow interactive access to the program's environment. That's basically the convenience of interpreters with the speed of binary compilation. Some compilers don't really compile, they just pre-digest and compress code. I heard a while back that's how Perl works. So sometimes the compiler is just doing a bit of the work and most of it is still interpretation.

最后，现在，解释和编译是一种权衡，花费(一次)编译的时间通常会获得更好的运行时性能，但解释环境提供了更多的交互机会。编译与解释主要是“理解”程序的工作如何在不同的过程之间划分的问题，而如今，由于语言和产品试图提供两者的最佳服务，这条界线有点模糊。

解释源代码相对于编译源代码的最大优势是可移植性。

如果你的源代码是编译的，你需要为你的程序运行在不同类型的处理器和/或平台编译不同的可执行文件(例如一个用于Windows x86，一个用于Windows x64，一个用于Linux x64，等等)。此外，除非您的代码完全符合标准，并且不使用任何特定于平台的函数/库，否则您实际上需要编写和维护多个代码库!

如果你的源代码是解释型的，你只需要编写一次，它就可以在任何平台上由合适的解释器解释和执行!它是便携!请注意，解释器本身是为特定平台编写和编译的可执行程序。

编译代码的一个优点是它向最终用户隐藏了源代码(可能是知识产权)，因为您部署的不是人类可读的原始源代码，而是一个模糊的二进制可执行文件。

语言本身既不编译也不解释，只有语言的特定实现才是。Java就是一个很好的例子。有一个基于字节码的平台(JVM)、一个本机编译器(gcj)和一个用于Java超集(bsh)的互用器。那么Java现在是什么呢?字节码编译，本机编译还是解释?

其他既编译又解释的语言有Scala、Haskell或Ocaml。每种语言都有一个交互式解释器，以及一个字节码或本机机器码的编译器。

所以一般来说，用“编译型”和“解释型”来划分语言并没有多大意义。

The Python Book©2015 Imagine Publishing Ltd，简单地通过第10页中提到的以下提示来区分差异:

像Python这样的解释型语言是指将源代码转换为机器码，然后在每次程序运行时执行的语言。这与编译语言(如C)不同，后者只将源代码转换为机器代码一次——然后在程序每次运行时执行生成的机器代码。