Dynamic code transformation systems (DCTS) can broadly be grouped into three distinct categories: optimization, translation and instrumentation. All of these face the critical challenge of minimizing the overhead incurred during transformation since their execution is interleaved with the execution of the application itself. The common DCTS tasks incurring overhead are the identification of frequently executed code sequences, costly analysis of program information, and run-time creation (writing) of new code sequences. The cost of such work is amortized by the repeated execution of the transformed code. However, as these steps are applied to all general code regions (regardless of their execution frequency and characteristics), there is substantial overhead that impacts the application’s performance. As such, it is challenging to effectively deploy dynamic transformation under fixed performance constraints. This paper explores a technique for eliminating the overhead incurred by exploiting persistent application execution characteristics that are shared across different application invocations. This technique is implemented and evaluated in Pin, a dynamic instrumentation engine. This version of Pin is referred to as Persistent Pin (PPin). Initial PPin experimental results indicate that using information from prior runs can reduce dynamic instrumentation overhead of SPEC applications by as much as 25% and over 90% for everyday applications like web browsers, display rendering systems, and spreadsheet programs.