A dynamic optimizer is a software-based system that performs code modifications at runtime, and several such systems have been proposed over the past several years. These systems typically perform optimization on the level of an instruction trace, and most use caching mechanisms to store recently optimized portions of code. Since the dynamic optimizers produce variable-length code traces that are modified copies of portions of the original executable, a code cache management scheme must deal with the difficult problem of caching objects that vary in size and cannot be subdivided without adding extra jump instructions. Because of these constraints, many dynamic optimizers have chosen unsophisticated schemes, such as flushing the entire cache when it becomes full. Flushing minimizes the overhead of cache management but tends to discard many useful traces. This paper evaluates several alternative cache management schemes that identify and remove only enough traces to make room for a new trace. We find that by treating the code cache as a circular buffer, we can reduce the code cache miss rate by half of that achieved by flushing. Furthermore, this approach adds very little bookkeeping overhead and avoids the problems associated with code cache fragmentation. These characteristics are extremely important in a dynamic system since more complex strategies will do more harm than good if the overhead is too high.