Biabduction (and related problems) in array separation logic

We investigate array separation logic (\mathsf {ASL}), a variant of symbolic-heap separation logic in which the data structures are either pointers or arrays, i.e., contiguous blocks of memory. This logic provides a language for compositional memory safety proofs of array programs. We focus on the biabduction problem for this logic, which has been established as the key to automatic specification inference at the industrial scale. We present an \mathsf {NP} decision procedure for biabduction in \mathsf {ASL}, and we also show that the problem of finding a consistent solution is \mathsf {NP}-hard. Along the way, we study satisfiability and entailment in \mathsf {ASL}, giving decision procedures and complexity bounds for both problems. We show satisfiability to be \mathsf {NP}-complete, and entailment to be decidable with high complexity. The surprising fact that biabduction is simpler than entailment is due to the fact that, as we show, the element of choice over biabduction solutions enables us to dramatically reduce the search space.

The final publication is available at Springer via https://doi.org/10.1007/978-3-319-63046-5_29

Cite this paper as:
Brotherston J., Gorogiannis N., Kanovich M. (2017) Biabduction (and Related Problems) in Array Separation Logic. In: de Moura L. (eds) Automated Deduction – CADE 26. CADE 2017. Lecture Notes in Computer Science, vol 10395. Springer, Cham