Fast Interprocedural Class Analysis

Previous algorithms for interprocedural control flow analysis of higher-order and/or object-oriented languages have been described that perform propagation or constraint satisfaction and take O(N3) time (such as Shivers’s 0-CFA and Heintze’s set-based analysis), or unification and take O(Nα(N,N)) time (such as Steensgaard’s pointer analysis), or optimistic reachability analysis and take O(N) time (such as Bacon and Sweeney’s Rapid Type Analysis). We describe a general parameterized analysis framework that integrates propagation-based and unification-based analysis primitives and optimistic reachability analysis, whose instances mimic these existing algorithms as well as several new algorithms taking O(N), O(Nα(N,N)), O(N2), and O(N2α(N,N)) time; our O(N) and O(Nα(N,N)) algorithms produce more precise results than the previous algorithms with these complexities. We implemented our algorithm framework in the Vortex optimizing compiler, and we measured the cost and benefit of these interprocedural analysis algorithms in practice on a collection of substantial Cecil and Java programs.

Fast Interprocedural Class Analysis

Previous algorithms for interprocedural control flow analysis of higher-order and/or object-oriented languages have been described that perform propagation or constraint satisfaction and take O(N 3 ) time (such as Shivers's 0-CFA and Heintze's setbased analysis), or unification and take O(Na(N,N)) time (such as Steensgaard's pointer analysis), or optimistic reachability analysis and take O(N) time (such as Bacon and Sweeney's Rapid Type Analysis). We describe a general parameterized analysis framework that integrates propagation-based and unification-based analysis primitives and optimistic reachability analysis, whose instances mimic these existing algorithms as well as several new algorithms taking O(N), O(Na(N,N)), O(N 2 ), and O(N 2 a(N,N)) time; our O(N) and O(Na(N,N)) algorithms produce more precise results than the previous algorithms with these complexities. We implemented our algorithm framework in the Vortex optimizing compiler, and we measured the cost and benefit of t..

Fast Interprocedural Class Analysis

Previous algorithms for interprocedural control flow analysis of higher-order and/or object-oriented languages have been described that perform propagation or constraint satisfaction and take O(N³) time (such as Shivers's 0-CFA and Heintze's setbased analysis), or unification and take O(Na(N,N)) time (such as Steensgaard's pointer analysis), or optimistic reachability analysis and take O(N) time (such as Bacon and Sweeney's Rapid Type Analysis). We describe a general parameterized analysis framework that integrates propagation-based and unification-based analysis primitives and optimistic reachability analysis, whose instances mimic these existing algorithms as well as several new algorithms taking O(N), O(Na(N,N)), O(N²), and O(N² a(N,N)) time; our O(N) and O(Na(N,N)) algorithms produce more precise results than the previous algorithms with these complexities. We implemented our algorithm framework in the Vortex optimizing compiler, and we measured the cost and benefit of t..

Vortex: An Optimizing Compiler for Object-Oriented Languages

Previously, techniques such as class hierarchy analysis and profile-guided receiver class prediction have been demonstrated to greatly improve the performance of applications written in pure object-oriented languages, but the degree to which these results are transferable to applications written in hybrid languages has been unclear. In part to answer this question, we have developed the Vortex compiler infrastructure, a language-independent optimizing compiler for object-oriented languages, with front-ends for Cecil, C++, Java, and Modula-3. In this paper, we describe the Vortex compiler's intermediate language, internal structure, and optimization suite, and then we report the results of experiments assessing the effectiveness of different combinations of optimizations on sizable applications across these four languages. We characterize the benchmark programs in terms of a collection of static and dynamic metrics, intended to quantify aspects of the "object-orientedness " of a program..