Context-free language (CFL) reachability is a fundamental framework widely used to model a variety of program analysis tasks, though it often suffers from inherent inefficiency due to its (sub)cubic time complexity.

In this paper, we propose a novel perspective, \emph{relation chaining}, which interprets CFL-reachability solving as the process of chaining labeled edges representing binary relations. This formulation exposes substantial derivation redundancy (in terms of frequent and repetitive chaining operations) arising from inefficient chaining strategies employed by existing approaches. To address this, we introduce SQUID, a new algorithm that incorporates two simple yet effective chaining techniques—\emph{adaptive chaining} and \emph{differential chaining}—built upon an enhanced graph representation. We have implemented SQUID as a standalone tool and evaluated it against two state-of-the-art CFL-reachability solvers and a leading Datalog solver across three key program analyses: field-sensitive alias analysis and context-sensitive value-flow analysis for C/C++, and field-sensitive points-to analysis for Java. Experimental results show that SQUID substantially improves the scalability of CFL-reachability solving by effectively reducing a large portion of redundant chaining operations.