Donald Bren School of Information and Computer Sciences

High-performance architectures rely upon powerful optimizing and parallelizing compilers to maximize performance. Such compilers need accurate program analysis to enable their performance-enhancing transformations. In the domain of program analysis for parallelization, pointer analysis is a difficult and increasingly common problem. When faced with dynamic, pointer-based data structures, existing solutions are either too limited in the types of data structures they can analyze, or require too much effort on the part of the programmer.

Recently we proposed a compromising approach, in which the programmer supplies some small amount of information, and the compiler performs the remaining analysis [HHN92a]. However, the language for conveying this information is unable to accurately describe a number of important data structures, and does not easily support the compiler's underlying alias analysis. In this paper we present a more powerful description language that also directly supports alias analysis. Ultimately, this will lead to more accurate program analysis for a larger class of programs, and hence the increased application of performance-enhancing transformations on these programs.