我猜这是计算机科学中最大的误解之一。 因为解释和编译是完全不同的两件事，我们不能用这种方式进行比较。

编译是将一种语言翻译成另一种语言的过程。编译的类型很少。

编译-将高级语言转换为机器/字节代码(例如:C/ c++ /Java) 翻译——将高级语言翻译成另一种高级语言(例如:TypeScript)

解释是实际执行程序的过程。这可能以几种不同的方式发生。

Machine level interpretation - This interpretation happens to the code which is compiled into machine code. Instructions are directly interpreted by the processor. Programming languages like C/C++ generate machine code, which is executable by the processor. So the processor can directly execute these instructions. Virtual machine level interpretation - This interpretation happens to the code which is not compiled into the machine level (processor support) code, but into some intermediate-level code. This execution is done by another software, which is executed by the processor. At this time actually processor doesn't see our application. It just executing the virtual machine, which is executing our application. Programming languages like Java, Python, C# generate a byte code, which is executable by the virtual interpreter/machine.

所以在一天结束的时候，我们必须明白的是，世界上所有的编程语言都应该在某个时候进行解释。它可以由处理器(硬件)或虚拟机完成。

编译只是将我们编写的人类可理解的高级代码带到机器可理解的硬件/软件级别的过程。

这是完全不同的两件事，我们无法比较。但是这些术语非常适合教给初学者编程语言是如何工作的。

PS: Some programming languages like Java have a hybrid approach to do this. First, compile the high-level code into byte code which is virtual-machine readable. And on the fly, a component called the JIT compiler compiles byte-code into machine code. Specifically, code lines that are executed again and again many times are get translated into the machine language, which makes the interpretation process much faster. Because hardware processor is always much faster than virtual interpreter/processor.

Java JIT编译器如何工作

开始用“过去的冲击波”来思考

很久很久以前，有一个计算机王国 解释器和编译器。的优点引起了各种各样的争论 一个比另一个。当时的普遍意见是这样的:

解释器:快速开发(编辑和运行)。执行速度慢，因为每个语句都必须被解释为 每次执行的机器代码(想想这对于执行了数千次的循环意味着什么)。 编译器:开发(编辑、编译、链接和运行)缓慢。编译/链接步骤可能会花费大量时间)。快 来执行。整个程序已经是原生机器代码了。

运行时有一到两个数量级的差异 解释程序和编译程序之间存在性能差异。其他的区别 点，例如代码的运行时可变性，也有一些兴趣，但主要是 区别围绕着运行时性能问题。

今天的情况已经发展到这样的程度，编译/解释的区别是 几乎无关紧要。许多 编译语言调用的运行时服务并非如此 完全基于机器代码。而且，大多数解释型语言都被“编译”成字节码 之前执行。字节码解释器非常高效，可以与一些编译器生成的解释器相匹敌 从执行速度的角度来看代码。

典型的区别是编译器生成本机机器码，解释器读取源代码 使用某种运行时系统动态生成机器代码。 如今，经典的诠释者已所剩无几——几乎全部 编译成字节码(或其他一些半编译状态)，然后在虚拟“机器”上运行。

我猜这是计算机科学中最大的误解之一。 因为解释和编译是完全不同的两件事，我们不能用这种方式进行比较。

编译是将一种语言翻译成另一种语言的过程。编译的类型很少。

编译-将高级语言转换为机器/字节代码(例如:C/ c++ /Java) 翻译——将高级语言翻译成另一种高级语言(例如:TypeScript)

解释是实际执行程序的过程。这可能以几种不同的方式发生。

Machine level interpretation - This interpretation happens to the code which is compiled into machine code. Instructions are directly interpreted by the processor. Programming languages like C/C++ generate machine code, which is executable by the processor. So the processor can directly execute these instructions. Virtual machine level interpretation - This interpretation happens to the code which is not compiled into the machine level (processor support) code, but into some intermediate-level code. This execution is done by another software, which is executed by the processor. At this time actually processor doesn't see our application. It just executing the virtual machine, which is executing our application. Programming languages like Java, Python, C# generate a byte code, which is executable by the virtual interpreter/machine.

所以在一天结束的时候，我们必须明白的是，世界上所有的编程语言都应该在某个时候进行解释。它可以由处理器(硬件)或虚拟机完成。

编译只是将我们编写的人类可理解的高级代码带到机器可理解的硬件/软件级别的过程。

这是完全不同的两件事，我们无法比较。但是这些术语非常适合教给初学者编程语言是如何工作的。

PS: Some programming languages like Java have a hybrid approach to do this. First, compile the high-level code into byte code which is virtual-machine readable. And on the fly, a component called the JIT compiler compiles byte-code into machine code. Specifically, code lines that are executed again and again many times are get translated into the machine language, which makes the interpretation process much faster. Because hardware processor is always much faster than virtual interpreter/processor.

Java JIT编译器如何工作

编译语言是这样一种语言:程序一旦编译，就用目标机器的指令来表达。例如，源代码中的加法“+”操作可以直接转换为机器代码中的“ADD”指令。

解释型语言是指指令不直接由目标机器执行，而是由其他程序(通常用本机语言编写)读取和执行的语言。例如，相同的“+”操作将在运行时被解释器识别，然后调用它自己的“add(a,b)”函数，并使用适当的参数，然后执行机器代码“add”指令。

你可以在编译语言中做你在解释语言中可以做的任何事情，反之亦然——它们都是图灵完备的。然而，这两种方法在实施和使用方面都有优点和缺点。

我将完全概括(纯粹主义者原谅我!)，但大致来说，以下是编译语言的优点:

通过直接使用目标计算机的本机代码获得更快的性能 有机会在编译阶段应用相当强大的优化

下面是解释型语言的优点:

更容易实现(编写好的编译器非常困难!!) 不需要运行编译阶段:可以直接“动态”执行代码 是否可以更方便地使用动态语言

注意，字节码编译等现代技术增加了一些额外的复杂性——这里发生的情况是，编译器的目标是一个与底层硬件不同的“虚拟机”。这些虚拟机指令可以在稍后阶段再次编译，以获得本机代码(例如，由Java JVM JIT编译器完成)。

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。

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.