Model Checking Embedded C Software Using k-Induction and Invariants

Rocha, Herbert; Ismail, Hussama; Cordeiro, Lucas C.; Barreto, Raimundo

doi:10.1007/978-1-4614-2266-2_7

Cited by 8 publications

(9 citation statements)

References 21 publications

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“…This effect is reduced by the previously reported discretization of the state-space; otherwise, the number of iterations is less than all other algorithms. Performance problems can be solved with further abstraction of the state space (e.g., intervals analysis) [33], or restricting it by imposing new restrictions on the variables, changing the intervals at each iteration.…”

Section: Resultsmentioning

confidence: 99%

“…However, the verification time of the present approach could be reduced with appropriate problem constraints and with the use of state-of-art verification techniques, e.g., abstraction interpretation [33]. Thus, this paper represents an important advance in SMT/SAT optimization techniques, paving the way for several future improvements.…”

Section: Discussionmentioning

confidence: 99%

“…Thus, this paper represents an important advance in SMT/SAT optimization techniques, paving the way for several future improvements. Future studies include the application of the present approach to autonomous vehicles navigation systems and enhancements in the model-checking procedure for reducing the verification time by means of multicore verification [13] and invariant generation [33], [36], in addition to compare the present approach to other optimization methods [37], [38].…”

Section: Discussionmentioning

confidence: 99%

See 2 more Smart Citations

SMT-based Verification Applied to Non-convex Optimization Problems

Araujo¹,

Bessa²,

Cordeiro³

et al. 2016

2016 VI Brazilian Symposium on Computing Systems Engineering (SBESC)

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This paper presents a novel, complete, and flexible optimization algorithm, which relies on recursive executions that re-constrains a model-checking procedure based on Satisfiability Modulo Theories (SMT). This SMT-based optimization technique is able to optimize a wide range of functions, including non-linear and non-convex problems using fixed-point arithmetic. Although SMT-based optimization is not a new technique, this work is the pioneer in solving non-linear and non-convex problems based on SMT; previous applications are only able to solve integer and rational linear problems. The proposed SMT-based optimization algorithm is compared to other traditional optimization techniques. Experimental results show the efficiency and effectiveness of the proposed algorithm, which finds the optimal solution in all evaluated benchmarks, while traditional techniques are usually trapped by local minima.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

SMT-based Verification Applied to Non-convex Optimization Problems

Araujo¹,

Bessa²,

Cordeiro³

et al. 2016

2016 VI Brazilian Symposium on Computing Systems Engineering (SBESC)

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“…This cost is insignificant for larger models but causes decreased performance for benchmarks consisting of many very small models. There are also other tools such as ESBMC-DepthK [100], VVT [101] CPAchecker, [102], CPROVER [103] attempting to prove C programs using similar techniques (k-induction, invariant generation, and PDR).…”

Section: Online Aivcmentioning

confidence: 99%

Inductive Validity Cores

Ghassabani

Whalen

Gacek

et al. 2021

IIEEE Trans. Software Eng.

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Symbolic model checkers can construct proofs of properties over very complex models. However, the results reported by the tool when a proof succeeds do not generally provide much insight to the user. It is often useful for users to have traceability information related to the proof: which portions of the model were necessary to construct it. This traceability information can be used to diagnose a variety of modeling problems such as overconstrained axioms and underconstrained properties, and can also be used to measure completeness of a set of requirements over a model. We propose the notion of inductive validity cores (IVCs), which are intended to trace a property to a minimal set of model elements necessary for proof. Such cores are not unique, and algorithms for efficiently producing both single IVC and all IVCs are presented. IVCs can be used for several interesting analyses, including regression analysis for testing/proof, determination of the minimum (as opposed to minimal) number of model elements necessary for proof, the diversity examination of model elements leading to proof, and analyzing fault tolerance.

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“…DepthK uses ESBMC, a context-bounded symbolic model checker that verifies single-and multi-threaded C programs [1,2], as its main verification engine. More specifically, it uses ESBMC either to find property violations up to a given bound k or to prove correctness by using the k-induction schema [3][4][5]. However, in contrast to the "plain" ESBMC, DepthK first infers program invariants using polyhedral constraints.…”

Section: Overviewmentioning

confidence: 99%

DepthK: A k-Induction Verifier Based on Invariant Inference for C Programs

Rocha

Ismail

et al. 2017

Tools and Algorithms for the Construction and Analysis of Systems

Self Cite

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DepthK is a software verification tool that employs a proof by induction algorithm that combines k-induction with invariant inference. In order to efficiently and effectively verify and falsify safety properties in C programs, DepthK infers program invariants using polyhedral constraints. Experimental results show that our approach can handle a wide variety of safety properties in several intricate verification tasks.

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Model Checking Embedded C Software Using k-Induction and Invariants

Cited by 8 publications

References 21 publications

SMT-based Verification Applied to Non-convex Optimization Problems

SMT-based Verification Applied to Non-convex Optimization Problems

Inductive Validity Cores

DepthK: A k-Induction Verifier Based on Invariant Inference for C Programs

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