The long-standing conflict between code optimization and symbolic debugging is examined. The effects of local and global optimizations on the variables of a program are categorized, and models for representing the effect of optimizations are given. Algorithms use these models to determine the subset of variables whose values do not correspond to those in the original program. Restoring these variables to their correct values is investigated, and empirical results from the application of these algorithms to local optimization are also presented.