This paper analyzed the execution of Java bytecode and direct threaded optimization technology of interpreter, proposed and implemented a new performance optimization solution of embedded Java VM based on direct threaded technology specially for ARM7 platform.
分析了Java字节码的解释执行和基于解释执行的DirectThreadedInterpreter性能优化技术。以DirectThreadedInterpreter为基础，提出并实现了一种针对ARM7平台的嵌入式Java虚拟机解释器性能优化方案。
But while the Python interpreter is running an application, Psyco sometimes checks to see if it can substitute some specialized machine code for regular Python bytecode actions.
但是当Python解释器运行应用程序时，Psyco会不时地检查，看是否能用一些专门的机器代码去替换常规的Python字节码操作。
This bytecode compilation model makes Python scripts portable and faster than a pure interpreter that runs raw source code lines. But it also makes Python slower than true compilers that translate source code to binary machine code.
这种字节码编译模型使得Python比其它纯粹解释型的脚本语言更加容易迁移平台，也更快，但也正因为如此，它比那些将源代码编译成二进制机器码的语言又来得慢。
Evan has added a JIT framework that can be enabled, along with a dynamically generated bytecode interpreter.
Evan加入了JIT架构，以及一个动态的字节码解释器。