Biabduction (and Related Problems) in Array Separation Logic

P. 472–490.

Kanovich M., Brotherston J., Gorogiannis N.

We investigate array separation logic (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 NPNP decision procedure for biabduction in ASL, and we also show that the problem of finding a consistent solution is NPNP-hard. Along the way, we study satisfiability and entailment in ASL, giving decision procedures and complexity bounds for both problems. We show satisfiability to be 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.

 

 

Keywords: complexity, entailment, separation logic, Arrays, Biabduction

Publication based on the results of: Explanation-oriented Methods of Data Analysis for Semantically Rich Data and Their Applications (2017)

In book

26th International Conference on Automated Deduction – CADE 26

Springer, 2017.