一句话：提出跨域交互的稀疏抽象执行，以提升指针分析与主数据流分析的精度。
稀疏静态分析先做快速指针分析过近似值流，再仅沿预计算值流稀疏传播数据流事实，以提升可扩展性。现有稀疏技术多关注主分析可扩展性，但其离线与主阶段的指针分析仅依赖单一内存地址域，未利用区间域等其他域的值，导致别名结果保守（如数组不敏感），限制主数据流分析精度。本文提出通过跨域交互实现精确的稀疏抽象执行，让不同抽象域协同刻画值流与别名，在保持稀疏分析可扩展性的同时提升主分析精度。摘要未给出具体实验结果；评估应检验精度改进及可扩展性保持。
Sparse static analysis offers a more scalable solution compared to its non-sparse counterpart. The basic idea is to first conduct a fast pointer analysis that over-approximates the value-flows and propagates the data-flow facts sparsely along only the pre-computed value-flows instead of all control flow points. Current sparse techniques focus on improving the scalability of the main analysis while maintaining its precision. However, their pointer analyses in both the offline and main phases are inherently imprecise because they rely solely on a single memory address domain without considering values from other domains like the interval domain. Consequently, this leads to conservative alias results, like arrayinsensitivity, which leaves substantial room for precision improvement of the main data-flow analysis.