Enhanced sharing analysis techniques: a comprehensive evaluation
Roberto Bagnara, Enea Zaffanella, Patricia M. Hill
Abstract
Sharing, an abstract domain developed by D. Jacobs and A. Langen for the analysis of logic programs, derives useful aliasing information. It is well-known that a commonly used core of techniques, such as the integration of Sharing with freeness and linearity information, can significantly improve the precision of the analysis. However, a number of other proposals for refined domain combinations have been circulating for years. One feature that is common to these proposals is that they do not seem to have undergone a thorough experimental evaluation even with respect to the expected precision gains. In this paper we experimentally evaluate: helping Sharing with the definitely ground variables found using Pos, the domain of positive Boolean formulas; the incorporation of explicit structural information; a full implementation of the reduced product of Sharing and Pos; the issue of reordering the bindings in the computation of the abstract mgu; an original proposal for the addition of a new mode recording the set of variables that are deemed to be ground or free; a refined way of using linearity to improve the analysis; the recovery of hidden information in the combination of Sharing with freeness information. Finally, we discuss the issue of whether tracking compoundness allows the computation of more sharing information.
Create a lesson
Related papers
How Often Does Your Program Fail?
Arnab Ray, Aalok Thakkar
Metamorphic Testing for Floating-Point Performance Issues in SMT Solvers
Rosa Abbasi, Eva Darulova
The Output-Space Hypothesis: Enumerative Equivalence Checking for Tensor Programs
Paul Biberstein, Joseph Devietti, Mayur Naik
Theories of Mind as Domain-Specific Languages of Thought
Kartik Chandra, Jonathan Ragan-Kelley, Joshua B. Tenenbaum et al.
LLVM Translation Validation Automated with Large Language Models and Lean
Chunhao Liao, Hongxu Xu, Xintong Zhou et al.
Splyce: SIMD Vectorization of Sparse Coiteration
Kabilan Mahathevan, Poorna Gunathilaka, Kirshanthan Sundararajah