Name
Abstract | ||
|---|---|---|
Automated software verification of concurrent programs is challenging because of exponentially growing state spaces. Verification techniques such as model checking need to explore a large number of possible executions that are possible under a non-deterministic scheduler. State space reduction techniques such as partial order reduction simplify the verification problem, however, the reduced state space may still be exponentially large and intractable. This paper discusses Iteratively Relaxed Scheduling, a framework that uses scheduling constraints in order to simplify the verification problem and enable automated verification of programs which could not be handled with fully non-deterministic scheduling. Program executions are safe as long as the same scheduling constraints are enforced under which the program has been verified, e.g., by instrumenting a program with additional synchronization. As strict enforcement of scheduling constraints may induce a high execution time overhead, we present optimizations over a naive solution that reduce this overhead. Our evaluation of a prototype implementation on well-known benchmark programs shows the effect of scheduling constraints on the execution time overhead and how this overhead can be reduced by relaxing and choosing constraints. |
Year | Venue | Field |
|---|---|---|
2018 | arXiv: Programming Languages | Synchronization,Programming language,Model checking,Scheduling (computing),Computer science,Execution time,Enforcement,Partial order reduction,State space,Distributed computing,Software verification |
DocType | Volume | Citations |
Journal | abs/1809.01955 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Patrick Metzler | 1 | 0 | 1.69 |
| Habib Saissi | 2 | 8 | 4.23 |
| Péter Bokor | 3 | 29 | 5.14 |
| Neeraj Suri | 4 | 1040 | 112.91 |