Safe and sound program analysis with Flix

Program development tools such as bug finders, build automation tools, compilers, debuggers, integrated development environments, and refactoring tools increasingly rely on static analysis techniques to reason about program behavior. Implementing such static analysis tools is a complex and difficult task with concerns about safety and soundness. Safety guarantees that the fixed point computation -- inherent in most static analyses -- converges and ultimately terminates with a deterministic result. Soundness guarantees that the computed result over-approximates the concrete behavior of the program under analysis. But how do we know if we can trust the result of the static analysis itself? Who will guard the guards? In this paper, we propose the use of automatic program verification techniques based on symbolic execution and SMT solvers to verify the correctness of the abstract domains used in static analysis tools. We implement a verification toolchain for Flix, a functional and logic programming language tailored for the implementation of static analyses. We apply this toolchain to several abstract domains. The experimental results show that we are able to prove 99.5% and 96.3% of the required safety and soundness properties, respectively.