Designing programming languages for analyzability: a fresh look at pointer data structures

1992 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Abstract In this paper we propose a programming language mechanism and associated compiler techniques which signiicantly enhance the analyzability of pointer-based data structures frequently used in non-scientiic programs. Our approach is based on exploiting two important properties of pointer data structures: structural inductivity and speculative traversability. Structural inductivity facilitates the application of a static interference analysis method for such pointer data structures based on path matrices, and speculative traversability is utilized by a novel loop unrolling technique for while loops that exploit ne-grain parallelism by speculatively traversing such data structures. The eeectiveness of this approach is demonstrated by applying it to a collection of loops found in typical non-scientiic C programs.