Name
Abstract | ||
|---|---|---|
Verification tasks frequently require deciding systems of linear constraints over modular (machine) arithmetic. Existing approaches for reasoning over modular arithmetic use bit-vector solvers, or else approximate machine integers with mathematical integers and use arithmetic solvers. Neither is ideal; the first is sound but inefficient, and the second is efficient but unsound. We describe a linear encoding which correctly describes modular arithmetic semantics, yielding an optimistic but sound approach. Our method abstracts the problem with linear arithmetic, but progressively refines the abstraction when modular semantics is violated. This preserves soundness while exploiting the mostly integer nature of the constraint problem. We present a prototype implementation, which gives encouraging experimental results. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/978-3-319-66263-3_24 | Lecture Notes in Computer Science |
Field | DocType | Volume |
Integer,Discrete mathematics,Combinatorics,Abstraction,Computer science,Modular arithmetic,Modular design,Soundness,Semantics,Benders' decomposition,Encoding (memory) | Conference | 10491 |
ISSN | Citations | PageRank |
0302-9743 | 0 | 0.34 |
References | Authors | |
17 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| bishoksan kafle | 1 | 39 | 7.88 |
| Graeme Gange | 2 | 137 | 24.27 |
| Peter Schachte | 3 | 256 | 22.76 |
| Harald Søndergaard | 4 | 858 | 79.52 |
| Peter J. Stuckey | 5 | 4368 | 457.58 |