Abstract Interpretation using a Language of Symbolic Approximation
This work addresses limitations in program analysis for embedded systems, though it appears incremental as it builds on existing abstract interpretation methods.
The authors tackled the problem of imprecise symbolic abstractions in traditional abstract interpretation frameworks for imperative programs by proposing a new framework based on symbolic expressions. They demonstrated its practical applicability by building a complete analyzer for embedded C programs.
The traditional abstract domain framework for imperative programs suffers from several shortcomings; in particular it does not allow precise symbolic abstractions. To solve these problems, we propose a new abstract interpretation framework, based on symbolic expressions used both as an abstraction of the program, and as the input analyzed by abstract domains. We demonstrate new applications of the frame- work: an abstract domain that efficiently propagates constraints across the whole program; a new formalization of functor domains as approximate translation, which allows the production of approximate programs, on which we can perform classical symbolic techniques. We used these to build a complete analyzer for embedded C programs, that demonstrates the practical applicability of the framework.