Abstract: Sophisticated static analysis techniques often have complicated implementations, much of which provides logic for tuning and scaling rather than basic analysis functionalities. This tight coupling of basic algorithms with special treatments for scalability makes an analysis implementation hard to (1) make correct, (2) understand/work with, and (3) reuse for other clients. This paper presents Chianina, a graph system we developed for fully context- and flow-sensitive analysis of large C programs. Chianina overcomes these challenges by allowing the developer to provide only the basic algorithm of an analysis and pushing the tuning/scaling work to the underlying system. Key to the success of Chianina is (1) an evolving graph formulation of flow sensitivity and (2) the leverage of out-of-core, disk support to deal with memory blowup resulting from context sensitivity. We implemented three context- and flow-sensitive analyses on top of Chianina and scaled them to large C programs like Linux (17M LoC) on a single commodity PC.