Many context-sensitive data flow analyses can be formulated as a variant of the all-pairs Dyck-CFL reachability problem, which, in general, is of sub-cubic time complexity and quadratic space complexity. Such high complexity significantly limits the scalability of context-sensitive data flow analysis and is not affordable for analyzing large-scale software. This paper presents \textsc{Flare}, a reduction from the CFL reachability problem to the conventional graph reachability problem for context-sensitive data flow analysis. This reduction allows us to benefit from recent advances in reachability indexing schemes, which often consume almost linear space for answering reachability queries in almost constant time. We have applied our reduction to a context-sensitive alias analysis and a context-sensitive information-flow analysis for C/C++ programs. Experimental results on standard benchmarks and open-source software demonstrate that we can achieve orders of magnitude speedup at the cost of only moderate space to store the indexes. The implementation of our approach is publicly available.

中文翻译：

---

索引上下文相关的可达性

许多上下文敏感的数据流分析可以表述为全对 Dyck-CFL 可达性问题的变体，通常，该问题具有亚三次时间复杂度和二次空间复杂度。如此高的复杂性极大地限制了上下文敏感数据流分析的可扩展性，并且对于分析大型软件来说是负担不起的。本文介绍了 \textsc{Flare}，这是从 CFL 可达性问题到用于上下文敏感数据流分析的传统图可达性问题的简化。这种减少使我们能够从可达性索引方案的最新进展中受益，这些方案通常消耗几乎线性的空间来在几乎恒定的时间内回答可达性查询。我们已经将我们的简化应用于 C/C++ 程序的上下文敏感别名分析和上下文敏感信息流分析。标准基准测试和开源软件的实验结果表明，我们可以以仅适度的空间来存储索引为代价实现数量级的加速。我们方法的实施是公开的。