Flow Sensitivity without Control Flow Graph: An Efficient Andersen-Style Flow-Sensitive Pointer Analysis

2025-03-25 · Source: cs.SE updates on arXiv.org · Field: Technology & Digital — Software Development & Engineering, Program Analysis, Compiler Design · Depth: Expert, extended

Summary

Cg-FsPta is a novel Flow-Sensitive Constraint Graph (FSConsG) based pointer analysis designed to overcome the computational inefficiencies of traditional control flow graph (CFG) based methods. This approach utilizes the structural advantages of set-constraint graphs, commonly used in flow-insensitive analysis, while preserving flow sensitivity for variable definitions and uses. By separating variable representation from control flow, Cg-FsPta enables the application of sophisticated graph optimization and dynamic solving techniques. Experimental evaluations on the SPEC CPU 2017 benchmark suite demonstrate that Cg-FsPta significantly enhances efficiency. It achieves an average memory reduction of 33.05% and accelerates flow-sensitive pointer analysis by 7.27x compared to the leading VSFS method, especially when integrated with the Sfr technique. With the Wave propagation algorithm, it still provides a 1.93x speedup and 23.99% memory reduction, all while maintaining analytical precision.

Key takeaway

For research scientists developing static analysis tools, or software engineers working on compiler optimizations, Cg-FsPta presents a compelling alternative to traditional flow-sensitive pointer analysis. Its novel Flow-Sensitive Constraint Graph (FSConsG) approach delivers substantial efficiency gains, reducing memory usage by up to 33.05% and accelerating analysis by up to 7.27x, while preserving precision. You should explore integrating FSConsG-based methods to enhance the scalability and performance of your program analysis frameworks, especially for large C/C++ codebases.

Key insights

Cg-FsPta achieves flow-sensitive pointer analysis precision with flow-insensitive efficiency by using a simplified constraint graph.

Principles

• Separate variable representation from control flow for efficiency.
• Encode flow-sensitivity via versioned address-taken variables.
• Store all constraint information exclusively on graph edges.

Method

Cg-FsPta constructs a Flow-Sensitive Constraint Graph (FSConsG) from LLVM-IR, flow-insensitive analysis results, and a CFG. It converts top-level operations to FSConsG edges and maintains def-use relations for address-taken variables via versioning, then solves points-to sets iteratively.

In practice

• Apply graph simplification (cycle elimination, folding) to FSConsG.
• Integrate with Andersen's Wave or Sfr algorithms for solving.
• Analyze large-scale C/C++ programs more efficiently.

Topics

• Program Analysis
• Static Analysis
• Pointer Analysis
• Flow-Sensitive Analysis
• Constraint Graphs
• LLVM Intermediate Representation
• Performance Optimization

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Editorial summary, takeaway, and curation by AIssential. Original article published by cs.SE updates on arXiv.org.