一句话：提出过程间分配环境（IDE）问题的符号特定稀疏化，利用变量状态独立性安全省略流函数计算以加速静态分析。
本文关注静态分析中过程间数据流求解的效率问题。已有的稀疏分析不再对控制流图每条边计算数据流，而是只沿定义-使用链传播；SparseDroid 进一步表明，污点分析因某个变量的污点状态不依赖其他变量，可以安全地省略更多流函数计算。本文在此基础上研究过程间分配环境（IDE）问题的符号特定稀疏化，目标是把这种按符号或按变量独立性的思想用于更一般的 IDE 数据流问题，在保持分析可靠性的同时减少不必要的流函数计算，从而提升稀疏静态分析的效果。给定摘要未报告具体实现与实验评估结果。
Previous work has shown that one can often greatly speed up static analysis by computing data flows not for every edge in the program's control-flow graph but instead only along definition-use chains. This yields a so-called sparse static analysis. Recent work on SparseDroid has shown that specifically taint analysis can be "sparsified" with extraordinary effectiveness because the taint state of one variable does not depend on those of others. This allows one to soundly omit more flow-function computations than in the general case.