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.

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。

首先，澄清一下，Java不是完全静态编译和以c++的方式链接的。它被编译成字节码，然后由JVM解释。JVM可以对本机机器语言进行即时编译，但不必这样做。

更重要的是:我认为交互性是主要的实际区别。由于所有内容都是解释的，所以您可以截取一小段代码，解析并根据环境的当前状态运行它。因此，如果您已经执行了初始化变量的代码，则可以访问该变量，等等。它真的很适合函数式风格。

然而，解释成本很高，特别是当您有一个包含大量引用和上下文的大型系统时。根据定义，这是一种浪费，因为相同的代码可能必须解释和优化两次(尽管大多数运行时都为此进行了缓存和优化)。不过，您仍然需要支付运行时成本，并且经常需要运行时环境。您也不太可能看到复杂的过程间优化，因为目前它们的性能还没有充分的交互性。

因此，对于不会有太大变化的大型系统，以及某些语言，更有意义的是预编译和预链接所有内容，做所有可以做的优化。最终会得到一个非常精简的运行时，该运行时已经针对目标机器进行了优化。

至于生成可执行文件，恕我直言，这一点关系不大。通常可以从编译语言创建可执行文件。但是您也可以使用解释语言创建可执行文件，只不过解释器和运行时已经打包在可执行文件中，并且对您隐藏了。这意味着您通常仍然需要支付运行时成本(尽管我确信对于某些语言，有方法将所有内容转换为可执行树)。

我不同意所有的语言都可以互动。某些语言，如C语言，与机器和整个链接结构紧密相连，我不确定您是否能够构建一个有意义的完整的交互式版本

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。

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。

很难给出一个实际的答案，因为差异在于语言定义本身。可以为每一种编译语言构建一个解释器，但不可能为每一种解释语言构建一个编译器。它主要是关于语言的正式定义。所以在大学里没有人喜欢理论信息学。