Dynamic optimization is emerging as a promising approach to overcome many of the obstacles of traditional static compilation. But while there are a number of compiler infrastructures for developing static optimizations, there are very few for developing dynamic optimizations. We present a framework for implementing dynamic analyses and optimizations. We provide an interface for building external modules, or clients, for the DynamoRIO dynamic code modification system. This interface abstracts away many low-level details of the DynamoRIO runtime system while exposing a simple and powerful, yet efficient and lightweight, API. This is achieved by restricting optimization units to linear streams of code and using adaptive levels of detail for representing instructions. The interface is not restricted to optimization and can be used for instrumentation, profiling, dynamic translation, etc.. To demonstrate

Conventional compilers are designed for producing highly optimized code without paying much attention to compile time. The design goals of Java just-in-time compilers are different: produce fast code at the smallest possible compile time. In this article we present a very fast algorithm for translating JavaVM byte code to high quality machine code for RISC processors. This algorithm handles combines instructions, does copy elimination and coalescing and does register allocation. It comprises three passes: basic block determination, stack analysis and register preallocation, final register allocation and machine code generation. This algorithm replaces an older one in the CACAO JavaVM implementation reducing the compile time by a factor of seven and producing slightly faster machine code. The speedup comes mainly from following simplifications: fixed assignment of registers at basic block boundaries, simple register allocator, better exception handling, better memory management and fine...

For domain specific languages, "scripting languages", dynamic languages, and for virtual machine-based languages, the most straightforward implementation strategy is to write an interpreter. A simple interpreter consists of a loop that fetches the next bytecode, dispatches to the routine handling that bytecode, then loops. There are many ways to improve upon this simple mechanism, but as long as the execution of the program is driven by a representation of the program other than as a stream of native instructions, there will be some "interpretive overhead".

The rapid increase in the use of the Internet in manyaspects of our lives has led to an explosive growth in the spread of malware such as computer worms, viruses,trojans, spyware, and bots. Software security considerations have accordingly become a crucial aspect ofmodern software design, development, and deployment. Since software--both new applications to be installedon a system and patches or upgrades to existing ones--is