Reducer-based construction of conditional verifiers

Beyer, Dirk; Jakobs, Marie-Christine; Lemberger, Thomas R.; Wehrheim, Heike

doi:10.1145/3180155.3180259

Cited by 31 publications

(43 citation statements)

References 53 publications

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“…(c n , l n ) of concrete states from the path. Note the we deviate here from the definition given in [14], where concrete executions do not contain information about the program locations. This is necessary here since we want to reason about the concrete executions that fulfill a given non-reachability specification, i.e., that never reach certain locations in the original program.…”

Section: Preliminariesmentioning

confidence: 98%

“…For the theoretical part, we will have to set a common ground for the concepts of verification witnesses [10,11] as well as reducers [14]. In both cases, programs are represented as control-flow automata (CFAs).…”

Section: Preliminariesmentioning

confidence: 99%

“…In case of a violation witness, which describes a path through the program to a specific program location, we transform the program such that all parts that are marked as unnecessary for the path by the witness are pruned. This is similar to the reducer for a condition in reducer-based conditional model checking [14]. In case of a correctness witness, which describes invariants that can be used in a correctness proof, we transform the program such that the invariants are asserted (to check that they really hold) and assumed (to use them in a re-constructed correctness proof).…”

Section: Introductionmentioning

confidence: 99%

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MetaVal: Witness Validation via Verification

Beyer

Spiessl

2020

Computer Aided Verification

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Witness validation is an important technique to increase trust in verification results, by making descriptions of error paths (violation witnesses) and important parts of the correctness proof (correctness witnesses) available in an exchangeable format. This way, the verification result can be validated independently from the verification in a second step. The problem is that there are unfortunately not many tools available for witness-based validation of verification results. We contribute to closing this gap with the approach of validation via verification, which is a way to automatically construct a set of validators from a set of existing verification engines. The idea is to take as input a specification, a program, and a verification witness, and produce a new specification and a transformed version of the original program such that the transformed program satisfies the new specification if the witness is useful to confirm the result of the verification. Then, an 'off-the-shelf' verifier can be used to validate the previously computed result (as witnessed by the verification witness) via an ordinary verification task. We have implemented our approach in the validator MetaVal, and it was successfully used in SV-COMP 2020 and confirmed 3 653 violation witnesses and 16 376 correctness witnesses. The results show that MetaVal improves the effectiveness (167 uniquely confirmed violation witnesses and 833 uniquely confirmed correctness witnesses) of the overall validation process, on a large benchmark set. All components and experimental data are publicly available.

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Section: Preliminariesmentioning

confidence: 98%

Section: Preliminariesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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MetaVal: Witness Validation via Verification

Beyer

Spiessl

2020

Computer Aided Verification

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“…Various combinations have been proposed for verification [2,10,11,14,25,27,[29][30][31]35,37,40,50,64] and test-suite generation [1,32,34,36,38,47,51,54,56,59,60,63]. We focus on combinations that interleave approaches.…”

Section: Related Workmentioning

confidence: 99%

“…Similarly, reachability tools like CPAchecker construct witnesses [6,7] from ARGs. Conditional model checking [10,14] constructs a condition from an ARG when a verifier gives up. The condition describes the remaining verification task and is used by a subsequent verifier to restrict its exploration.…”

Section: Related Workmentioning

confidence: 99%

CoVeriTest: Cooperative Verifier-Based Testing

Beyer

Jakobs

2019

Fundamental Approaches to Software Engineering

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Testing is a widely used method to assess software quality. Coverage criteria and coverage measurements are used to ensure that the constructed test suites adequately test the given software. Since manually developing such test suites is too expensive in practice, various automatic test-generation approaches were proposed. Since all approaches come with different strengths, combinations are necessary in order to achieve stronger tools. We study cooperative combinations of verification approaches for test generation, with high-level information exchange. We present CoVeriTest, a hybrid approach for test-case generation, which iteratively applies different conditional model checkers. Thereby, it allows to adjust the level of cooperation and to assign individual time budgets per verifier. In our experiments, we combine explicit-state model checking and predicate abstraction (from CPAchecker) to systematically study different CoVeriTest configurations. Moreover, CoVeriTest achieves higher coverage than state-of-the-art test-generation tools for some programs.

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Conditional Testing

Beyer

Lemberger

2019

Automated Technology for Verification and Analysis

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Reducer-based construction of conditional verifiers

Cited by 31 publications

References 53 publications

MetaVal: Witness Validation via Verification

MetaVal: Witness Validation via Verification

CoVeriTest: Cooperative Verifier-Based Testing

Conditional Testing

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