Witnessing Network Transformations

Deng, Chaoqiang; Namjoshi, Kedar S.

doi:10.1007/978-3-319-67531-2_10

Cited by 2 publications

(1 citation statement)

References 14 publications

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“…However, all these model checking approaches do not provide an explanation on why a property is satisfied, by means of a certificate or proof. Although several works have tackled this problem [3,46,42,41,25,14], they aim mostly to automate proof reproducibility rather than actually helping the design process and they usually produce deductive proofs which are different from the topological proofs presented in this paper.…”

Section: Related Workmentioning

confidence: 99%

Integrating Topological Proofs with Model Checking to Instrument Iterative Design

Menghi

Rizzi

Bernasconi

2020

Fundamental Approaches to Software Engineering

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System development is not a linear, one-shot process. It proceeds through refinements and revisions. To support assurance that the system satisfies its requirements, it is desirable that continuous verification can be performed after each refinement or revision step. To achieve practical adoption, formal system modeling and verification must accommodate continuous verification efficiently and effectively. Our proposal to address this problem is TOrPEDO, a verification approach where models are given via Partial Kripke Structures (PKSs) and requirements are specified as Linear-time Temporal Logic (LTL) properties. PKSs support refinement, by deliberately indicating unspecified parts of the model that are later completed. We support verification in two complementary forms: via model checking and proofs. Model checking is useful to provide counterexamples, i.e., pinpoint model behaviors that violate requirements. Proofs are instead useful since they can explain why requirements are satisfied. In our work, we introduce a specific concept of proof, called topological proof (TP). A TP produces a slice of the original PKS which justifies the property satisfaction. Because models can be incomplete, TOrPEDO supports reasoning on requirements satisfaction, violation, and possible satisfaction (in the case where the satisfaction depends on unknown parts).

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Section: Related Workmentioning

confidence: 99%

Integrating Topological Proofs with Model Checking to Instrument Iterative Design

Menghi

Rizzi

Bernasconi

2020

Fundamental Approaches to Software Engineering

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TOrPEDO: witnessing model correctness with topological proofs

et al. 2021

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Model design is not a linear, one-shot process. It proceeds through refinements and revisions. To effectively support developers in generating model refinements and revisions, it is desirable to have some automated support to verify evolvable models. To address this problem, we recently proposed to adopt topological proofs, which are slices of the original model that witness property satisfaction. We implemented , a framework that provides automated support for using topological proofs during model design. Our results showed that topological proofs are significantly smaller than the original models, and that, in most of the cases, they allow the property to be re-verified by relying only on a simple syntactic check. However, our results also show that the procedure that computes topological proofs, which requires extracting unsatisfiable cores of LTL formulae, is computationally expensive. For this reason, currently handles models with a small dimension. With the intent of providing practical and efficient support for flexible model design and wider adoption of our framework, in this paper, we propose an enhanced—re-engineered—version of . The new version of relies on a novel procedure to extract topological proofs, which has so far represented the bottleneck of performances. We implemented our procedure within by considering Partial Kripke Structures (PKSs) and Linear-time Temporal Logic (LTL): two widely used formalisms to express models with uncertain parts and their properties. To extract topological proofs, the new version of converts the LTL formulae into an SMT instance and reuses an existing SMT solver (e.g., Microsoft ) to compute an unsatisfiable core. Then, the unsatisfiable core returned by the SMT solver is automatically processed to generate the topological proof. We evaluated by assessing (i) how does the size of the proofs generated by compares to the size of the models being analyzed; and (ii) how frequently the use of the topological proof returned by avoids re-executing the model checker. Our results show that provides proofs that are smaller ($$\approx $$ ≈ 60%) than their respective initial models effectively supporting designers in creating model revisions. In a significant number of cases ($$\approx $$ ≈ 79%), the topological proofs returned by enable assessing the property satisfaction without re-running the model checker. We evaluated our new version of by assessing (i) how it compares to the previous one; and (ii) how useful it is in supporting the evaluation of alternative design choices of (small) model instances in applied domains. The results show that the new version of is significantly more efficient than the previous one and can compute topological proofs for models with less than 40 states within two hours. The topological proofs and counterexamples provided by are useful to support the development of alternative design choices of (small) model instances in applied domains.

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Witnessing Network Transformations

Cited by 2 publications

References 14 publications

Integrating Topological Proofs with Model Checking to Instrument Iterative Design

Integrating Topological Proofs with Model Checking to Instrument Iterative Design

TOrPEDO: witnessing model correctness with topological proofs

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