The ART of Sharing Points-to Analysis (Extended Abstract)
Shashin Halalingaiah, Vijay Sundaresan, Daryl Maier, and V. Krishna, Nandivada

TL;DR
This paper introduces ART, a novel scheme for encoding and sharing precise points-to analysis results between tools, enhancing trust and efficiency in static analysis and compilation workflows.
Contribution
We propose ART, a new encoding scheme that allows safe, efficient sharing of flow-sensitive, context-insensitive points-to analysis results across independent tools.
Findings
ART encoding is concise and efficient.
The scheme enables safe regeneration of analysis results.
Implementation shows effectiveness on benchmark suites.
Abstract
Data-flow analyses like points-to analysis can vastly improve the precision of other analyses, and help perform powerful code optimizations. However, whole-program points-to analysis of large programs tend to be expensive - both in terms of time and memory. Consequently, many compilers (both static and JIT) and program-analysis tools tend to employ faster - but more conservative - points-to analysis to improve usability. As an alternative to such trading of precision for performance, various techniques have been proposed to perform precise yet expensive fixed-point points-to analyses ahead of time in a static analyzer, store the results, and then transmit them to independent compilation/program-analysis stages that may need them. However, an underlying concern of safety affects all such techniques - can a compiler (or program analysis tool) trust the points-to analysis results generated…
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