Computing the Similarity of Profiling Data

. We present a technique to measure and detect changes in the behavioral patterns of applications. In a continually dynamically optimizing system, such information is useful not only to decide which program parts to optimize, but also which previously optimized program parts to re-optimize. This leads to a system that is better tailored towards users' needs than statically optimized systems. 1 Introduction Lately, several systems have been proposed for dynamic program optimization. These systems no longer optimize applications at compile time but rather perform optimizations incrementally while the code is being executed. Besides being able to optimize portable applications (e.g., Java binaries), these systems have additional uncontested advantages: they enable intermodular optimizations and allow optimizations to take into account "up-to-the-minute" profiling data, which often enhances the code quality beyond what is commonly achievable with static compilation. One of the key issues..