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2 papers accepted at ASE 2024: BenchCloud and CoVeriTeam GUI

Funding by DFG-CONVEY

Articles in journal or book chapters

  1. Dirk Beyer, Po-Chun Chien, Marek Jankola, and Nian-Ze Lee. A Transferability Study of Interpolation-Based Hardware Model Checking for Software Verification. Proc. ACM Softw. Eng., 1(FSE), 2024. ACM. doi:10.1145/3660797 Link to this entry Keyword(s): CPAchecker, Software Model Checking Funding: DFG-CONVEY Publisher's Version PDF Presentation Supplement
    Artifact(s)
    Abstract
    Assuring the correctness of computing systems is fundamental to our society and economy, and formal verification is a class of techniques approaching this issue with mathematical rigor. Researchers have invented numerous algorithms to automatically prove whether a computational model, e.g., a software program or a hardware digital circuit, satisfies its specification. In the past two decades, Craig interpolation has been widely used in both hardware and software verification. Despite the similarities in the theoretical foundation between hardware and software verification, previous works usually evaluate interpolation-based algorithms on only one type of verification tasks (e.g., either circuits or programs), so the conclusions of these studies do not necessarily transfer to different types of verification tasks. To investigate the transferability of research conclusions from hardware to software, we adopt two performant approaches of interpolation-based hardware model checking, (1) Interpolation-Sequence-Based Model Checking (Vizel and Grumberg, 2009) and (2) Intertwined Forward-Backward Reachability Analysis Using Interpolants (Vizel, Grumberg, and Shoham, 2013), for software verification. We implement the algorithms proposed by the two publications in the software verifier CPAchecker because it has a software-verification adoption of the first interpolation-based algorithm for hardware model checking from 2003, which the two publications use as a comparison baseline. To assess whether the claims in the two publications transfer to software verification, we conduct an extensive experiment on the largest publicly available suite of safety-verification tasks for the programming language C. Our experimental results show that the important characteristics of the two approaches for hardware model checking are transferable to software verification, and that the cross-disciplinary algorithm adoption is beneficial, as the approaches adopted from hardware model checking were able to tackle tasks unsolvable by existing methods. This work consolidates the knowledge in hardware and software verification and provides open-source implementations to improve the understanding of the compared interpolation-based algorithms.
    BibTeX Entry
    @article{ItpTransfer-PACMSE, author = {Dirk Beyer and Po-Chun Chien and Marek Jankola and Nian-Ze Lee}, title = {A Transferability Study of Interpolation-Based Hardware Model Checking for Software Verification}, journal = {Proc. ACM Softw. Eng.}, volume = {1}, number = {FSE}, year = {2024}, publisher = {ACM}, doi = {10.1145/3660797}, url = {https://www.sosy-lab.org/research/dar-ismc-transferability/}, presentation = {https://www.sosy-lab.org/research/prs/2024-07-18_FSE_A_Transferability_Study_of_Interpolation-Based_HWMC_for_SV_Marek.pdf}, abstract = {Assuring the correctness of computing systems is fundamental to our society and economy, and <em>formal verification</em> is a class of techniques approaching this issue with mathematical rigor. Researchers have invented numerous algorithms to automatically prove whether a computational model, e.g., a software program or a hardware digital circuit, satisfies its specification. In the past two decades, <em>Craig interpolation</em> has been widely used in both hardware and software verification. Despite the similarities in the theoretical foundation between hardware and software verification, previous works usually evaluate interpolation-based algorithms on only one type of verification tasks (e.g., either circuits or programs), so the conclusions of these studies do not necessarily transfer to different types of verification tasks. To investigate the transferability of research conclusions from hardware to software, we adopt two performant approaches of interpolation-based hardware model checking, (1) <em>Interpolation-Sequence-Based Model Checking</em> (<a href="https://doi.org/10.1109/FMCAD.2009.5351148">Vizel and Grumberg, 2009</a>) and (2) <em>Intertwined Forward-Backward Reachability Analysis Using Interpolants</em> (<a href="https://doi.org/10.1007/978-3-642-36742-7_22">Vizel, Grumberg, and Shoham, 2013</a>), for software verification. We implement the algorithms proposed by the two publications in the software verifier CPAchecker because it has a software-verification adoption of the first interpolation-based algorithm for hardware model checking from 2003, which the two publications use as a comparison baseline. To assess whether the claims in the two publications transfer to software verification, we conduct an extensive experiment on the largest publicly available suite of safety-verification tasks for the programming language C. Our experimental results show that the important characteristics of the two approaches for hardware model checking are transferable to software verification, and that the cross-disciplinary algorithm adoption is beneficial, as the approaches adopted from hardware model checking were able to tackle tasks unsolvable by existing methods. This work consolidates the knowledge in hardware and software verification and provides open-source implementations to improve the understanding of the compared interpolation-based algorithms.}, keyword = {CPAchecker,Software Model Checking}, _pdf = {https://www.sosy-lab.org/research/pub/2024-FSE.A_Transferability_Study_of_Interpolation-Based_Hardware_Model_Checking_for_Software_Verification.pdf}, annote = {This article received the "ACM SIGSOFT Distinguished Paper Award" and its reproduction artifact received the "ACM SIGSOFT Best Artifact Award" at <a href="https://2024.esec-fse.org/info/awards">FSE 2024</a>!}, articleno = {90}, artifact = {10.5281/zenodo.11070973}, funding = {DFG-CONVEY}, issue_date = {July 2024}, numpages = {23}, }
    Additional Infos
    This article received the "ACM SIGSOFT Distinguished Paper Award" and its reproduction artifact received the "ACM SIGSOFT Best Artifact Award" at FSE 2024!
  2. Dirk Beyer, Matthias Kettl, and Thomas Lemberger. Decomposing Software Verification using Distributed Summary Synthesis. Proc. ACM Softw. Eng., 1(FSE), 2024. ACM. doi:10.1145/3660766 Link to this entry Keyword(s): CPAchecker, Software Model Checking Funding: DFG-CONVEY, DFG-COOP Publisher's Version PDF Supplement
    Artifact(s)
    Abstract
    There are many approaches for automated software verification, but they are either imprecise, do not scale well to large systems, or do not sufficiently leverage parallelization. This hinders the integration of software model checking into the development process (continuous integration). We propose an approach to decompose one large verification task into multiple smaller, connected verification tasks, based on blocks in the program control flow. For each block, summaries are computed — based on independent, distributed, continuous refinement by communication between the blocks. The approach iteratively synthesizes preconditions to assume at the block entry (which program states reach this block) and verification conditions to check at the block exit (which program states lead to a specification violation). This separation of concerns leads to an architecture in which all blocks can be analyzed in parallel, as independent verification problems. Whenever new information (as a precondition or verification condition) is available from other blocks, the verification can decide to restart with this new information. We realize our approach as an extension of the configurable-program-analysis algorithm and implement it for the verification of C programs in the widely used verifier CPAchecker. A large experimental evaluation shows the potential of our new approach: The distribution of the workload to several processing units works well and there is a significant reduction of the response time when using multiple processing units. There are even cases in which the new approach beats the highly-tuned, existing single-threaded predicate abstraction.
    BibTeX Entry
    @article{DSS-PACMSE, author = {Dirk Beyer and Matthias Kettl and Thomas Lemberger}, title = {Decomposing Software Verification using Distributed Summary Synthesis}, journal = {Proc. ACM Softw. Eng.}, volume = {1}, number = {FSE}, year = {2024}, publisher = {ACM}, doi = {10.1145/3660766}, url = {https://www.sosy-lab.org/research/distributed-summary-synthesis/}, presentation = {}, abstract = {There are many approaches for automated software verification, but they are either imprecise, do not scale well to large systems, or do not sufficiently leverage parallelization. This hinders the integration of software model checking into the development process (continuous integration). We propose an approach to decompose one large verification task into multiple smaller, connected verification tasks, based on blocks in the program control flow. For each block, summaries are computed — based on independent, distributed, continuous refinement by communication between the blocks. The approach iteratively synthesizes preconditions to assume at the block entry (which program states reach this block) and verification conditions to check at the block exit (which program states lead to a specification violation). This separation of concerns leads to an architecture in which all blocks can be analyzed in parallel, as independent verification problems. Whenever new information (as a precondition or verification condition) is available from other blocks, the verification can decide to restart with this new information. We realize our approach as an extension of the configurable-program-analysis algorithm and implement it for the verification of C programs in the widely used verifier CPAchecker. A large experimental evaluation shows the potential of our new approach: The distribution of the workload to several processing units works well and there is a significant reduction of the response time when using multiple processing units. There are even cases in which the new approach beats the highly-tuned, existing single-threaded predicate abstraction.}, keyword = {CPAchecker,Software Model Checking}, _pdf = {https://www.sosy-lab.org/research/pub/2024-FSE.Decomposing_Software_Verification_using_Distributed_Summary_Synthesis.pdf}, articleno = {90}, artifact = {10.5281/zenodo.11095864}, funding = {DFG-CONVEY,DFG-COOP}, issue_date = {July 2024}, numpages = {23}, }

Articles in conference or workshop proceedings

  1. Salih Ates, Dirk Beyer, Po-Chun Chien, and Nian-Ze Lee. MoXIchecker: An Extensible Model Checker for MoXI. In Proc. VSTTE, 2024. Springer. Link to this entry Keyword(s): Btor2 Funding: DFG-CONVEY, DFG-BRIDGE PDF Supplement
    Artifact(s)
    Abstract
    MoXI is a new intermediate verification language introduced in 2024 to promote the standardization and open-source implementations for symbolic model checking by extending the SMT-LIB 2 language with constructs to define state-transition systems. The tool suite of MoXI provides a translator from MoXI to Btor2, which is a lower-level intermediate language for hardware verification, and a translation-based model checker, which invokes mature hardware model checkers for Btor2 to analyze the translated verification tasks. The extensibility of such a translation-based model checker is restricted because more complex theories, such as integer or real arithmetics, cannot be precisely expressed with bit-vectors of fixed lengths in Btor2. We present MoXIchecker, the first model checker that solves MoXI verification tasks directly. Instead of translating MoXI to lower-level languages, MoXIchecker uses the solver-agnostic library PySMT for SMT solvers as backend for its verification algorithms. MoXIchecker is extensible because it accommodates verification tasks involving more complex theories, not limited by lower-level languages, facilitates the implementation of new algorithms, and is solver-agnostic by using the API of PySMT. In our evaluation, MoXIchecker uniquely solved tasks that use integer or real arithmetics, and achieved a comparable performance against the translation-based model checker from the MoXI tool suite.
    BibTeX Entry
    @inproceedings{VSTTE24, author = {Salih Ates and Dirk Beyer and Po-Chun Chien and Nian-Ze Lee}, title = {{MoXIchecker}: {An} Extensible Model Checker for {MoXI}}, booktitle = {Proc.\ VSTTE}, pages = {}, year = {2024}, series = {}, publisher = {Springer}, doi = {}, url = {https://www.sosy-lab.org/research/moxichecker/}, pdf = {https://www.sosy-lab.org/research/pub/2024-VSTTE.MoXIchecker_An_Extensible_Model_Checker_for_MoXI.pdf}, presentation = {}, abstract = {MoXI is a new intermediate verification language introduced in 2024 to promote the standardization and open-source implementations for symbolic model checking by extending the SMT-LIB 2 language with constructs to define state-transition systems. The tool suite of MoXI provides a translator from MoXI to Btor2, which is a lower-level intermediate language for hardware verification, and a translation-based model checker, which invokes mature hardware model checkers for Btor2 to analyze the translated verification tasks. The extensibility of such a translation-based model checker is restricted because more complex theories, such as integer or real arithmetics, cannot be precisely expressed with bit-vectors of fixed lengths in Btor2. We present MoXIchecker, the first model checker that solves MoXI verification tasks directly. Instead of translating MoXI to lower-level languages, MoXIchecker uses the solver-agnostic library PySMT for SMT solvers as backend for its verification algorithms. MoXIchecker is extensible because it accommodates verification tasks involving more complex theories, not limited by lower-level languages, facilitates the implementation of new algorithms, and is solver-agnostic by using the API of PySMT. In our evaluation, MoXIchecker uniquely solved tasks that use integer or real arithmetics, and achieved a comparable performance against the translation-based model checker from the MoXI tool suite.}, keyword = {Btor2}, artifact = {10.5281/zenodo.13895872}, funding = {DFG-CONVEY, DFG-BRIDGE}, }
  2. Dirk Beyer, Po-Chun Chien, and Marek Jankola. BenchCloud: A Platform for Scalable Performance Benchmarking. In Proc. ASE, pages 2386-2389, 2024. ACM. doi:10.1145/3691620.3695358 Link to this entry Keyword(s): Benchmarking, Competition on Software Verification (SV-COMP), Competition on Software Testing (Test-Comp) Funding: DFG-CONVEY, DFG-COOP Publisher's Version PDF Presentation Video Supplement
    Artifact(s)
    Abstract
    Performance evaluation is a crucial method for assessing automated-reasoning tools. Evaluating automated tools requires rigorous benchmarking to accurately measure resource consumption, including time and memory, which are essential for understanding the tools' capabilities. BenchExec, a widely used benchmarking framework, reliably measures resource usage for tools executed locally on a single node. This paper describes BenchCloud, a solution for elastic and scalable job distribution across hundreds of nodes, enabling large-scale experiments on distributed and heterogeneous computing environments. BenchCloud seamlessly integrates with BenchExec, allowing BenchExec to delegate the actual execution to BenchCloud. The system has been employed in several prominent international competitions in automated reasoning, including SMT-COMP, SV-COMP, and Test-Comp, underscoring its importance in rigorous tool evaluation across various research domains. It helps to ensure both internal and external validity of the experimental results. This paper presents an overview of BenchCloud's architecture and high- lights its primary use cases in facilitating scalable benchmarking.
    Demonstration video: https://youtu.be/aBfQytqPm0U
    Running system: https://benchcloud.sosy-lab.org/
    BibTeX Entry
    @inproceedings{ASE24a, author = {Dirk Beyer and Po-Chun Chien and Marek Jankola}, title = {{BenchCloud}: {A} Platform for Scalable Performance Benchmarking}, booktitle = {Proc.\ ASE}, pages = {2386-2389}, year = {2024}, series = {}, publisher = {ACM}, doi = {10.1145/3691620.3695358}, url = {https://benchcloud.sosy-lab.org/}, pdf = {https://www.sosy-lab.org/research/pub/2024-ASE24.BenchCloud_A_Platform_for_Scalable_Performance_Benchmarking.pdf}, presentation = {https://www.sosy-lab.org/research/prs/2024-10-30_ASE_BenchCloud_A_Platform_for_Scalable_Performance_Benchmarking_Po-Chun.pdf}, abstract = {Performance evaluation is a crucial method for assessing automated-reasoning tools. Evaluating automated tools requires rigorous benchmarking to accurately measure resource consumption, including time and memory, which are essential for understanding the tools' capabilities. BenchExec, a widely used benchmarking framework, reliably measures resource usage for tools executed locally on a single node. This paper describes BenchCloud, a solution for elastic and scalable job distribution across hundreds of nodes, enabling large-scale experiments on distributed and heterogeneous computing environments. BenchCloud seamlessly integrates with BenchExec, allowing BenchExec to delegate the actual execution to BenchCloud. The system has been employed in several prominent international competitions in automated reasoning, including SMT-COMP, SV-COMP, and Test-Comp, underscoring its importance in rigorous tool evaluation across various research domains. It helps to ensure both internal and external validity of the experimental results. This paper presents an overview of BenchCloud's architecture and high- lights its primary use cases in facilitating scalable benchmarking. <br> Demonstration video: <a href="https://youtu.be/aBfQytqPm0U">https://youtu.be/aBfQytqPm0U</a> <br> Running system: <a href="https://benchcloud.sosy-lab.org/">https://benchcloud.sosy-lab.org/</a>}, keyword = {Benchmarking, Competition on Software Verification (SV-COMP), Competition on Software Testing (Test-Comp)}, artifact = {10.5281/zenodo.13742756}, funding = {DFG-CONVEY, DFG-COOP}, video = {https://youtu.be/aBfQytqPm0U}, }
  3. Dirk Beyer, Thomas Lemberger, and Henrik Wachowitz. CPA-Daemon: Mitigating Tool Restarts for Java-Based Verifiers. In Proceedings of the 22nd International Symposium on Automated Technology for Verification and Analysis (ATVA 2024, Kyoto, Japan, October 21-24), LNCS , 2024. Springer. Link to this entry Keyword(s): CPAchecker, Software Model Checking, Cooperative Verification Funding: DFG-CONVEY PDF
    Artifact(s)
    BibTeX Entry
    @inproceedings{ATVA24, author = {Dirk Beyer and Thomas Lemberger and Henrik Wachowitz}, title = {{CPA-Daemon}: Mitigating Tool Restarts for Java-Based Verifiers}, booktitle = {Proceedings of the 22nd International Symposium on Automated Technology for Verification and Analysis (ATVA~2024, Kyoto, Japan, October 21-24)}, pages = {}, year = {2024}, series = {LNCS~}, publisher = {Springer}, pdf = {https://www.sosy-lab.org/research/pub/2024-ATVA.CPA-Daemon_Mitigating_Tool_Restart_for_Java-Based_Verifiers.pdf}, abstract = {}, keyword = {CPAchecker, Software Model Checking, Cooperative Verification}, artifact = {https://doi.org/10.5281/zenodo.11147333}, doinone = {Unpublished: Last checked: 2024-10-01}, funding = {DFG-CONVEY}, }
  4. Daniel Baier, Dirk Beyer, Po-Chun Chien, Marie-Christine Jakobs, Marek Jankola, Matthias Kettl, Nian-Ze Lee, Thomas Lemberger, Marian Lingsch-Rosenfeld, Henrik Wachowitz, and Philipp Wendler. Software Verification with CPAchecker 3.0: Tutorial and User Guide. In Proceedings of the 26th International Symposium on Formal Methods (FM 2024, Milan, Italy, September 9-13), LNCS 14934, pages 543-570, 2024. Springer. doi:10.1007/978-3-031-71177-0_30 Link to this entry Keyword(s): CPAchecker, Software Model Checking, Software Testing Funding: DFG-COOP, DFG-CONVEY, DFG-IDEFIX Publisher's Version PDF Presentation Supplement
    Artifact(s)
    Abstract
    This tutorial provides an introduction to CPAchecker for users. CPAchecker is a flexible and configurable framework for software verification and testing. The framework provides many abstract domains, such as BDDs, explicit values, intervals, memory graphs, and predicates, and many program-analysis and model-checking algorithms, such as abstract interpretation, bounded model checking, Impact, interpolation-based model checking, k-induction, PDR, predicate abstraction, and symbolic execution. This tutorial presents basic use cases for CPAchecker in formal software verification, focusing on its main verification techniques with their strengths and weaknesses. An extended version also shows further use cases of CPAchecker for test-case generation and witness-based result validation. The envisioned readers are assumed to possess a background in automatic formal verification and program analysis, but prior knowledge of CPAchecker is not required. This tutorial and user guide is based on CPAchecker in version 3.0. This user guide's latest version and other documentation are available at https://cpachecker.sosy-lab.org/doc.php.
    BibTeX Entry
    @inproceedings{FM24a, author = {Daniel Baier and Dirk Beyer and Po-Chun Chien and Marie-Christine Jakobs and Marek Jankola and Matthias Kettl and Nian-Ze Lee and Thomas Lemberger and Marian Lingsch-Rosenfeld and Henrik Wachowitz and Philipp Wendler}, title = {Software Verification with {CPAchecker} 3.0: {Tutorial} and User Guide}, booktitle = {Proceedings of the 26th International Symposium on Formal Methods (FM~2024, Milan, Italy, September 9-13)}, pages = {543-570}, year = {2024}, series = {LNCS~14934}, publisher = {Springer}, doi = {10.1007/978-3-031-71177-0_30}, url = {https://cpachecker.sosy-lab.org}, pdf = {https://www.sosy-lab.org/research/pub/2024-FM.Software_Verification_with_CPAchecker_3.0_Tutorial_and_User_Guide.pdf}, presentation = {https://www.sosy-lab.org/research/prs/2024-09-10_FM24_CPAchecker_Tutorial.pdf}, abstract = {This tutorial provides an introduction to CPAchecker for users. CPAchecker is a flexible and configurable framework for software verification and testing. The framework provides many abstract domains, such as BDDs, explicit values, intervals, memory graphs, and predicates, and many program-analysis and model-checking algorithms, such as abstract interpretation, bounded model checking, Impact, interpolation-based model checking, <i>k</i>-induction, PDR, predicate abstraction, and symbolic execution. This tutorial presents basic use cases for CPAchecker in formal software verification, focusing on its main verification techniques with their strengths and weaknesses. An extended version also shows further use cases of CPAchecker for test-case generation and witness-based result validation. The envisioned readers are assumed to possess a background in automatic formal verification and program analysis, but prior knowledge of CPAchecker is not required. This tutorial and user guide is based on CPAchecker in version 3.0. This user guide's latest version and other documentation are available at <a href="https://cpachecker.sosy-lab.org/doc.php">https://cpachecker.sosy-lab.org/doc.php</a>.}, keyword = {CPAchecker, Software Model Checking, Software Testing}, annote = {An <a href="https://www.sosy-lab.org/research/bib/All/index.html#TechReport24c">extended version</a> of this article is available on <a href="https://doi.org/10.48550/arXiv.2409.02094">arXiv</a>.}, artifact = {10.5281/zenodo.13612338}, funding = {DFG-COOP, DFG-CONVEY, DFG-IDEFIX}, }
    Additional Infos
    An extended version of this article is available on arXiv.
  5. Dirk Beyer, Po-Chun Chien, and Nian-Ze Lee. Augmenting Interpolation-Based Model Checking with Auxiliary Invariants. In Proceedings of the 30th International Symposium on Model Checking Software (SPIN 2024, Luxembourg City, Luxembourg, April 10-11), LNCS 14624, pages 227-247, 2024. Springer. doi:10.1007/978-3-031-66149-5_13 Link to this entry Keyword(s): Software Model Checking, Cooperative Verification, CPAchecker Funding: DFG-CONVEY Publisher's Version PDF Presentation Supplement
    Artifact(s)
    Abstract
    Software model checking is a challenging problem, and generating relevant invariants is a key factor in proving the safety properties of a program. Program invariants can be obtained by various approaches, including lightweight procedures based on data-flow analysis and intensive techniques using Craig interpolation. Although data-flow analysis runs efficiently, it often produces invariants that are too weak to prove the properties. By contrast, interpolation-based approaches build strong invariants from interpolants, but they might not scale well due to expensive interpolation procedures. Invariants can also be injected into model-checking algorithms to assist the analysis. Invariant injection has been studied for many well-known approaches, including k-induction, predicate abstraction, and symbolic execution. We propose an augmented interpolation-based verification algorithm that injects external invariants into interpolation-based model checking (McMillan, 2003), a hardware model-checking algorithm recently adopted for software verification. The auxiliary invariants help prune unreachable states in Craig interpolants and confine the analysis to the reachable parts of a program. We implemented the proposed technique in the verification framework CPAchecker and evaluated it against mature SMT-based methods in CPAchecker as well as other state-of-the-art software verifiers. We found that injecting invariants reduces the number of interpolation queries needed to prove safety properties and improves the run-time efficiency. Consequently, the proposed invariant-injection approach verified difficult tasks that none of its plain version (i.e., without invariants), the invariant generator, or any compared tools could solve.
    BibTeX Entry
    @inproceedings{SPIN24c, author = {Dirk Beyer and Po-Chun Chien and Nian-Ze Lee}, title = {Augmenting Interpolation-Based Model Checking with Auxiliary Invariants}, booktitle = {Proceedings of the 30th International Symposium on Model Checking Software (SPIN~2024, Luxembourg City, Luxembourg, April 10-11)}, pages = {227-247}, year = {2024}, series = {LNCS~14624}, publisher = {Springer}, doi = {10.1007/978-3-031-66149-5_13}, url = {https://www.sosy-lab.org/research/imc-df/}, pdf = {https://www.sosy-lab.org/research/pub/2024-SPIN.Augmenting_Interpolation-Based_Model_Checking_with_Auxiliary_Invariants.pdf}, presentation = {https://www.sosy-lab.org/research/prs/2024-04-10_SPIN_Augmenting_IMC_with_Auxiliary_Invariants_Po-Chun.pdf}, abstract = {Software model checking is a challenging problem, and generating relevant invariants is a key factor in proving the safety properties of a program. Program invariants can be obtained by various approaches, including lightweight procedures based on data-flow analysis and intensive techniques using Craig interpolation. Although data-flow analysis runs efficiently, it often produces invariants that are too weak to prove the properties. By contrast, interpolation-based approaches build strong invariants from interpolants, but they might not scale well due to expensive interpolation procedures. Invariants can also be injected into model-checking algorithms to assist the analysis. Invariant injection has been studied for many well-known approaches, including <i>k</i>-induction, predicate abstraction, and symbolic execution. We propose an augmented interpolation-based verification algorithm that injects external invariants into interpolation-based model checking (McMillan, 2003), a hardware model-checking algorithm recently adopted for software verification. The auxiliary invariants help prune unreachable states in Craig interpolants and confine the analysis to the reachable parts of a program. We implemented the proposed technique in the verification framework CPAchecker and evaluated it against mature SMT-based methods in CPAchecker as well as other state-of-the-art software verifiers. We found that injecting invariants reduces the number of interpolation queries needed to prove safety properties and improves the run-time efficiency. Consequently, the proposed invariant-injection approach verified difficult tasks that none of its plain version (i.e., without invariants), the invariant generator, or any compared tools could solve.}, keyword = {Software Model Checking, Cooperative Verification, CPAchecker}, annote = {This article received the "Best Paper Award" at SPIN 2024! An <a href="https://www.sosy-lab.org/research/bib/All/index.html#TechReport24a">extended version</a> of this article is available on <a href="https://doi.org/10.48550/arXiv.2403.07821">arXiv</a>.}, artifact = {10.5281/zenodo.10548594}, funding = {DFG-CONVEY}, }
    Additional Infos
    This article received the "Best Paper Award" at SPIN 2024! An extended version of this article is available on arXiv.
  6. Dirk Beyer, Matthias Kettl, and Thomas Lemberger. Fault Localization on Verification Witnesses. In Proceedings of the 30th International Symposium on Model Checking Software (SPIN 2024, Luxembourg City, Luxembourg, April 10-11), LNCS 14624, pages 205-224, 2024. Springer. doi:10.1007/978-3-031-66149-5_12 Link to this entry Keyword(s): Software Model Checking, Witness-Based Validation, CPAchecker Funding: DFG-CONVEY, DFG-IDEFIX, DFG-COOP Publisher's Version PDF
    Artifact(s)
    Abstract
    When verifiers report an alarm, they export a violation witness (exchangeable counterexample) that helps validate the reachability of that alarm. Conventional wisdom says that this violation witness should be very precise: the ideal witness describes a single error path for the validator to check. But we claim that verifiers overshoot and produce large witnesses with information that makes validation unnecessarily difficult. To check our hypothesis, we reduce violation witnesses to that information that automated fault-localization approaches deem relevant for triggering the reported alarm in the program. We perform a large experimental evaluation on the witnesses produced in the International Competition on Software Verification (SV-COMP 2023). It shows that our reduction shrinks the witnesses considerably and enables the confirmation of verification results that were not confirmable before.
    BibTeX Entry
    @inproceedings{SPIN24b, author = {Dirk Beyer and Matthias Kettl and Thomas Lemberger}, title = {Fault Localization on Verification Witnesses}, booktitle = {Proceedings of the 30th International Symposium on Model Checking Software (SPIN~2024, Luxembourg City, Luxembourg, April 10-11)}, pages = {205-224}, year = {2024}, series = {LNCS~14624}, publisher = {Springer}, doi = {10.1007/978-3-031-66149-5_12}, pdf = {https://sosy-lab.org/research/pub/2024-SPIN.Fault_Localization_on_Verification_Witnesses.pdf}, abstract = {When verifiers report an alarm, they export a violation witness (exchangeable counterexample) that helps validate the reachability of that alarm. Conventional wisdom says that this violation witness should be very precise: the ideal witness describes a single error path for the validator to check. But we claim that verifiers overshoot and produce large witnesses with information that makes validation unnecessarily difficult. To check our hypothesis, we reduce violation witnesses to that information that automated fault-localization approaches deem relevant for triggering the reported alarm in the program. We perform a large experimental evaluation on the witnesses produced in the International Competition on Software Verification (SV-COMP 2023). It shows that our reduction shrinks the witnesses considerably and enables the confirmation of verification results that were not confirmable before.}, keyword = {Software Model Checking, Witness-Based Validation, CPAchecker}, annote = {Nominated for best paper.<br> This work was also presented with a poster at the 46th International Conference on Software Engineering (ICSE 2024, Lisbon, Portugal, April 14-20): <a href="https://sosy-lab.org/research/pst/2024-03-05_ICSE24_Fault_Localization_on_Verification_Witnesses_Poster.pdf">Extended Abstract</a>.}, artifact = {10.5281/zenodo.10794627}, funding = {DFG-CONVEY,DFG-IDEFIX,DFG-COOP}, }
    Additional Infos
    Nominated for best paper.
    This work was also presented with a poster at the 46th International Conference on Software Engineering (ICSE 2024, Lisbon, Portugal, April 14-20): Extended Abstract.
  7. Paulína Ayaziová, Dirk Beyer, Marian Lingsch-Rosenfeld, Martin Spiessl, and Jan Strejček. Software Verification Witnesses 2.0. In Proceedings of the 30th International Symposium on Model Checking Software (SPIN 2024, Luxembourg City, Luxembourg, April 10-11), LNCS 14624, pages 184-203, 2024. Springer. doi:10.1007/978-3-031-66149-5_11 Link to this entry Keyword(s): Software Model Checking, Cooperative Verification, Witness-Based Validation, Witness-Based Validation (main), CPAchecker Funding: DFG-CONVEY, DFG-IDEFIX Publisher's Version PDF Presentation Supplement
    Artifact(s)
    BibTeX Entry
    @inproceedings{SPIN24a, author = {Paulína Ayaziová and Dirk Beyer and Marian Lingsch-Rosenfeld and Martin Spiessl and Jan Strejček}, title = {Software Verification Witnesses 2.0}, booktitle = {Proceedings of the 30th International Symposium on Model Checking Software (SPIN~2024, Luxembourg City, Luxembourg, April 10-11)}, pages = {184-203}, year = {2024}, series = {LNCS~14624}, publisher = {Springer}, doi = {10.1007/978-3-031-66149-5_11}, url = {https://gitlab.com/sosy-lab/benchmarking/sv-witnesses/}, pdf = {https://www.sosy-lab.org/research/pub/2024-SPIN.Software_Verification_Witnesses_2.0.pdf}, presentation = {https://www.sosy-lab.org/research/prs/2024-04-11_SPIN24_Software-Verification-Witnesses-2.0.pdf}, abstract = {}, keyword = {Software Model Checking, Cooperative Verification, Witness-Based Validation, Witness-Based Validation (main), CPAchecker}, annote = {}, artifact = {10.5281/zenodo.10826204}, funding = {DFG-CONVEY,DFG-IDEFIX}, }
  8. Daniel Baier, Dirk Beyer, Po-Chun Chien, Marek Jankola, Matthias Kettl, Nian-Ze Lee, Thomas Lemberger, Marian Lingsch-Rosenfeld, Martin Spiessl, Henrik Wachowitz, and Philipp Wendler. CPAchecker 2.3 with Strategy Selection (Competition Contribution). In Proceedings of the 30th International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS 2024, Luxembourg, Luxembourg, April 6-11), part 3, LNCS 14572, pages 359-364, 2024. Springer. doi:10.1007/978-3-031-57256-2_21 Link to this entry Keyword(s): Software Model Checking, Witness-Based Validation, CPAchecker Funding: DFG-CONVEY, DFG-IDEFIX Publisher's Version PDF Supplement
    Artifact(s)
    Abstract
    CPAchecker is a versatile framework for software verification, rooted in the established concept of configurable program analysis. Compared to the last published system description at SV-COMP 2015, the CPAchecker submission to SV-COMP 2024 incorporates new analyses for reachability safety, memory safety, termination, overflows, and data races. To combine forces of the available analyses in CPAchecker and cover the full spectrum of the diverse program characteristics and specifications in the competition, we use strategy selection to predict a sequential portfolio of analyses that is suitable for a given verification task. The prediction is guided by a set of carefully picked program features. The sequential portfolios are composed based on expert knowledge and consist of bit-precise analyses using k-induction, data-flow analysis, SMT solving, Craig interpolation, lazy abstraction, and block-abstraction memoization. The synergy of various algorithms in CPAchecker enables support for all properties and categories of C programs in SV-COMP 2024 and contributes to its success in many categories. CPAchecker also generates verification witnesses in the new YAML format.
    BibTeX Entry
    @inproceedings{TACAS24c, author = {Daniel Baier and Dirk Beyer and Po-Chun Chien and Marek Jankola and Matthias Kettl and Nian-Ze Lee and Thomas Lemberger and Marian Lingsch-Rosenfeld and Martin Spiessl and Henrik Wachowitz and Philipp Wendler}, title = {{CPAchecker} 2.3 with Strategy Selection (Competition Contribution)}, booktitle = {Proceedings of the 30th International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS~2024, Luxembourg, Luxembourg, April 6-11), part~3}, pages = {359-364}, year = {2024}, series = {LNCS~14572}, publisher = {Springer}, doi = {10.1007/978-3-031-57256-2_21}, url = {https://cpachecker.sosy-lab.org/}, abstract = {CPAchecker is a versatile framework for software verification, rooted in the established concept of configurable program analysis. Compared to the last published system description at SV-COMP 2015, the CPAchecker submission to SV-COMP 2024 incorporates new analyses for reachability safety, memory safety, termination, overflows, and data races. To combine forces of the available analyses in CPAchecker and cover the full spectrum of the diverse program characteristics and specifications in the competition, we use strategy selection to predict a sequential portfolio of analyses that is suitable for a given verification task. The prediction is guided by a set of carefully picked program features. The sequential portfolios are composed based on expert knowledge and consist of bit-precise analyses using <i>k</i>-induction, data-flow analysis, SMT solving, Craig interpolation, lazy abstraction, and block-abstraction memoization. The synergy of various algorithms in CPAchecker enables support for all properties and categories of C programs in SV-COMP 2024 and contributes to its success in many categories. CPAchecker also generates verification witnesses in the new YAML format.}, keyword = {Software Model Checking, Witness-Based Validation, CPAchecker}, _pdf = {https://www.sosy-lab.org/research/pub/2024-TACAS.CPAchecker_2.3_with_Strategy_Selection_Competition_Contribution.pdf}, artifact = {10.5281/zenodo.10203297}, funding = {DFG-CONVEY, DFG-IDEFIX}, }
  9. Dirk Beyer. State of the Art in Software Verification and Witness Validation: SV-COMP 2024. In B. Finkbeiner and L. Kovács, editors, Proceedings of the 30th International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS 2024, Luxembourg, Luxembourg, April 6-11), part 3, LNCS 14572, pages 299-329, 2024. Springer. doi:10.1007/978-3-031-57256-2_15 Link to this entry Keyword(s): Competition on Software Verification (SV-COMP), Competition on Software Verification (SV-COMP Report), Software Model Checking Funding: DFG-CONVEY Publisher's Version PDF Supplement
    BibTeX Entry
    @inproceedings{TACAS24b, author = {Dirk Beyer}, title = {State of the Art in Software Verification and Witness Validation: {SV-COMP 2024}}, booktitle = {Proceedings of the 30th International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS~2024, Luxembourg, Luxembourg, April 6-11), part~3}, editor = {B.~Finkbeiner and L.~Kovács}, pages = {299-329}, year = {2024}, series = {LNCS~14572}, publisher = {Springer}, doi = {10.1007/978-3-031-57256-2_15}, sha256 = {}, url = {https://sv-comp.sosy-lab.org/2024/}, keyword = {Competition on Software Verification (SV-COMP),Competition on Software Verification (SV-COMP Report),Software Model Checking}, _pdf = {https://www.sosy-lab.org/research/pub/2024-TACAS.State_of_the_Art_in_Software_Verification_and_Witness_Validation_SV-COMP_2024.pdf}, funding = {DFG-CONVEY}, }
  10. Zsófia Ádám, Dirk Beyer, Po-Chun Chien, Nian-Ze Lee, and Nils Sirrenberg. Btor2-Cert: A Certifying Hardware-Verification Framework Using Software Analyzers. In Proc. TACAS (3), LNCS 14572, pages 129-149, 2024. Springer. doi:10.1007/978-3-031-57256-2_7 Link to this entry Keyword(s): Software Model Checking, Witness-Based Validation, Cooperative Verification, Btor2 Funding: DFG-CONVEY Publisher's Version PDF Supplement
    Artifact(s)
    Abstract
    Formal verification is essential but challenging: Even the best verifiers may produce wrong verification verdicts. Certifying verifiers enhance the confidence in verification results by generating a witness for other tools to validate the verdict independently. Recently, translating the hardware-modeling language Btor2 to software, such as the programming language C or LLVM intermediate representation, has been actively studied and facilitated verifying hardware designs by software analyzers. However, it remained unknown whether witnesses produced by software verifiers contain helpful information about the original circuits and how such information can aid hardware analysis. We propose a certifying and validating framework Btor2-Cert to verify safety properties of Btor2 circuits, combining Btor2-to-C translation, software verifiers, and a new witness validator Btor2-Val, to answer the above open questions. Btor2-Cert translates a software violation witness to a Btor2 violation witness; As the Btor2 language lacks a format for correctness witnesses, we encode invariants in software correctness witnesses as Btor2 circuits. The validator Btor2-Val checks violation witnesses by circuit simulation and correctness witnesses by validation via verification. In our evaluation, Btor2-Cert successfully utilized software witnesses to improve quality assurance of hardware. By invoking the software verifier CBMC on translated programs, it uniquely solved, with confirmed witnesses, 8% of the unsafe tasks for which the hardware verifier ABC failed to detect bugs.
    BibTeX Entry
    @inproceedings{TACAS24a, author = {Zsófia Ádám and Dirk Beyer and Po-Chun Chien and Nian-Ze Lee and Nils Sirrenberg}, title = {{Btor2-Cert}: {A} Certifying Hardware-Verification Framework Using Software Analyzers}, booktitle = {Proc.\ TACAS~(3)}, pages = {129-149}, year = {2024}, series = {LNCS~14572}, publisher = {Springer}, doi = {10.1007/978-3-031-57256-2_7}, url = {https://www.sosy-lab.org/research/btor2-cert/}, abstract = {Formal verification is essential but challenging: Even the best verifiers may produce wrong verification verdicts. Certifying verifiers enhance the confidence in verification results by generating a witness for other tools to validate the verdict independently. Recently, translating the hardware-modeling language Btor2 to software, such as the programming language C or LLVM intermediate representation, has been actively studied and facilitated verifying hardware designs by software analyzers. However, it remained unknown whether witnesses produced by software verifiers contain helpful information about the original circuits and how such information can aid hardware analysis. We propose a certifying and validating framework Btor2-Cert to verify safety properties of Btor2 circuits, combining Btor2-to-C translation, software verifiers, and a new witness validator Btor2-Val, to answer the above open questions. Btor2-Cert translates a software violation witness to a Btor2 violation witness; As the Btor2 language lacks a format for correctness witnesses, we encode invariants in software correctness witnesses as Btor2 circuits. The validator Btor2-Val checks violation witnesses by circuit simulation and correctness witnesses by validation via verification. In our evaluation, Btor2-Cert successfully utilized software witnesses to improve quality assurance of hardware. By invoking the software verifier CBMC on translated programs, it uniquely solved, with confirmed witnesses, 8&percnt; of the unsafe tasks for which the hardware verifier ABC failed to detect bugs.}, keyword = {Software Model Checking, Witness-Based Validation, Cooperative Verification, Btor2}, _pdf = {https://www.sosy-lab.org/research/pub/2024-TACAS.Btor2-Cert_A_Certifying_Hardware-Verification_Framework_Using_Software_Analyzers.pdf}, annote = {The reproduction package of this article received the "Distinguished Artifact Award" at TACAS 2024!}, artifact = {10.5281/zenodo.10548597}, funding = {DFG-CONVEY}, }
    Additional Infos
    The reproduction package of this article received the "Distinguished Artifact Award" at TACAS 2024!
  11. Thomas Lemberger and Henrik Wachowitz. CoVeriTeam GUI: A No-Code Approach to Cooperative Software Verification. In Proceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering (ASE 2024, Sacramento, CA, USA, October 27-November 1), pages 2419-2422, 2024. doi:10.1145/3691620.3695366 Link to this entry Keyword(s): Software Model Checking, Cooperative Verification Funding: DFG-CONVEY Publisher's Version PDF
    Artifact(s)
    Abstract
    We present CoVeriTeam GUI, a No-Code web frontend to compose new software-verification workflows from existing analysis techniques. Verification approaches stopped relying on single techniques years ago, and instead combine selections that complement each other well. So far, such combinations were-under high implementation and maintenance cost-glued together with proprietary code. Now, CoVeriTeam GUI enables users to build new verification workflows without programming. Verification techniques can be combined through various composition operators in a drag-and-drop fashion directly in the browser, and an integration with a remote service allows to execute the built workflows with the click of a button. CoVeriTeam GUI is available open source under Apache 2.0: https://gitlab.com/sosy-lab/software/coveriteam-gui
    Demonstration video: https://youtu.be/oZoOARuIOuA
    BibTeX Entry
    @inproceedings{CoVeriTeamGUI-ASE24, author = {Thomas Lemberger and Henrik Wachowitz}, title = {CoVeriTeam GUI: A No-Code Approach to Cooperative Software Verification}, booktitle = {Proceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering (ASE 2024, Sacramento, CA, USA, October 27-November 1)}, pages = {2419-2422}, year = {2024}, doi = {10.1145/3691620.3695366}, pdf = {https://www.sosy-lab.org/research/pub/2024-ASE24.CoVeriTeam_GUI_A_No-Code_Approach_to_Cooperative_Software_Verification.pdf}, presentation = {}, abstract = {We present CoVeriTeam GUI, a No-Code web frontend to compose new software-verification workflows from existing analysis techniques. Verification approaches stopped relying on single techniques years ago, and instead combine selections that complement each other well. So far, such combinations were---under high implementation and maintenance cost---glued together with proprietary code. Now, CoVeriTeam GUI enables users to build new verification workflows without programming. Verification techniques can be combined through various composition operators in a drag-and-drop fashion directly in the browser, and an integration with a remote service allows to execute the built workflows with the click of a button. CoVeriTeam GUI is available open source under Apache 2.0: <a href="https://gitlab.com/sosy-lab/software/coveriteam-gui">https://gitlab.com/sosy-lab/software/coveriteam-gui</a><br> Demonstration video: <a href="https://youtu.be/oZoOARuIOuA">https://youtu.be/oZoOARuIOuA</a>}, keyword = {Software Model Checking, Cooperative Verification}, artifact = {10.5281/zenodo.13757771}, funding = {DFG-CONVEY}, }
  12. Po-Chun Chien and Nian-Ze Lee. CPV: A Circuit-Based Program Verifier (Competition Contribution). In Proc. TACAS, LNCS 14572, pages 365-370, 2024. Springer. doi:10.1007/978-3-031-57256-2_22 Link to this entry Keyword(s): Software Model Checking, Cooperative Verification, Btor2 Funding: DFG-CONVEY Publisher's Version PDF Presentation Supplement
    Artifact(s)
    Abstract
    We submit to SV-COMP 2024 CPV, a circuit-based software verifier for C programs. CPV utilizes sequential circuits as its intermediate representation and invokes hardware model checkers to analyze the reachability safety of C programs. As the frontend, it uses Kratos2, a recently proposed verification tool, to translate a C program to a sequential circuit. As the backend, state-of-the-art hardware model checkers ABC and AVR are employed to verify the translated circuits. We configure the hardware model checkers to run various analyses, including IC3/PDR, interpolation-based model checking, and k-induction. Information discovered by hardware model checkers is represented as verification witnesses. In the competition, CPV achieved comparable performance against participants whose intermediate representations are based on control-flow graphs. In the category ReachSafety, it outperformed several mature software verifiers as a first-year participant. CPV manifests the feasibility of sequential circuits as an alternative intermediate representation for program analysis and enables head-to-head algorithmic comparison between hardware and software verification.
    BibTeX Entry
    @inproceedings{CPV-TACAS24, author = {Po-Chun Chien and Nian-Ze Lee}, title = {CPV: A Circuit-Based Program Verifier (Competition Contribution)}, booktitle = {Proc.\ TACAS}, pages = {365-370}, year = {2024}, series = {LNCS~14572}, publisher = {Springer}, doi = {10.1007/978-3-031-57256-2_22}, url = {https://gitlab.com/sosy-lab/software/cpv}, pdf = {https://www.sosy-lab.org/research/pub/2024-TACAS.CPV_A_Circuit-Based_Program_Verifier_Competition_Contribution.pdf}, presentation = {https://www.sosy-lab.org/research/prs/2024-04-08_SVCOMP_CPV_A_Circuit-Based_Program_Verifier_Po-Chun.pdf}, abstract = {We submit to SV-COMP 2024 CPV, a circuit-based software verifier for C programs. CPV utilizes sequential circuits as its intermediate representation and invokes hardware model checkers to analyze the reachability safety of C programs. As the frontend, it uses Kratos2, a recently proposed verification tool, to translate a C program to a sequential circuit. As the backend, state-of-the-art hardware model checkers ABC and AVR are employed to verify the translated circuits. We configure the hardware model checkers to run various analyses, including IC3/PDR, interpolation-based model checking, and <i>k</i>-induction. Information discovered by hardware model checkers is represented as verification witnesses. In the competition, CPV achieved comparable performance against participants whose intermediate representations are based on control-flow graphs. In the category <i>ReachSafety</i>, it outperformed several mature software verifiers as a first-year participant. CPV manifests the feasibility of sequential circuits as an alternative intermediate representation for program analysis and enables head-to-head algorithmic comparison between hardware and software verification.}, keyword = {Software Model Checking, Cooperative Verification, Btor2}, artifact = {10.5281/zenodo.10203472}, funding = {DFG-CONVEY}, }
  13. Dirk Beyer, Po-Chun Chien, and Nian-Ze Lee. CPA-DF: A Tool for Configurable Interval Analysis to Boost Program Verification. In Proc. ASE, pages 2050-2053, 2023. IEEE. doi:10.1109/ASE56229.2023.00213 Link to this entry Keyword(s): Software Model Checking, Cooperative Verification, CPAchecker Funding: DFG-CONVEY Publisher's Version PDF Presentation Video Supplement
    Artifact(s)
    Abstract
    Software verification is challenging, and auxiliary program invariants are used to improve the effectiveness of verification approaches. For instance, the k-induction implementation in CPAchecker, an award-winning framework for program analysis, uses invariants produced by a configurable data-flow analysis to strengthen induction hypotheses. This invariant generator, CPA-DF, uses arithmetic expressions over intervals as its abstract domain and is able to prove some safe verification tasks alone. After extensively evaluating CPA-DF on SV-Benchmarks, the largest publicly available suite of C safety-verification tasks, we discover that its potential as a stand-alone analysis or a sub-analysis in a parallel portfolio for combined verification approaches has been significantly underestimated: (1) As a stand-alone analysis, CPA-DF finds almost as many proofs as the plain k-induction implementation without auxiliary invariants. (2) As a sub-analysis running in parallel to the plain k-induction implementation, CPA-DF boosts the portfolio verifier to solve a comparable amount of tasks as the heavily-optimized k-induction implementation with invariant injection. Our detailed analysis reveals that dynamic precision adjustment is crucial to the efficiency and effectiveness of CPA-DF. To generalize our results beyond CPAchecker, we use CoVeriTeam, a platform for cooperative verification, to compose three portfolio verifiers that execute CPA-DF and three other software verifiers in parallel, respectively. Surprisingly, running CPA-DF merely in parallel to these state-of-the-art tools further boosts the number of correct results up to more than 20%.
    Demonstration video: https://youtu.be/l7UG-vhTL_4
    BibTeX Entry
    @inproceedings{ASE23a, author = {Dirk Beyer and Po-Chun Chien and Nian-Ze Lee}, title = {{CPA-DF}: {A} Tool for Configurable Interval Analysis to Boost Program Verification}, booktitle = {Proc.\ ASE}, pages = {2050-2053}, year = {2023}, series = {}, publisher = {IEEE}, doi = {10.1109/ASE56229.2023.00213}, url = {https://www.sosy-lab.org/research/cpa-df/}, pdf = {https://www.sosy-lab.org/research/pub/2023-ASE.CPA-DF_A_Tool_for_Configurable_Interval_Analysis_to_Boost_Program_Verification.pdf}, presentation = {https://www.sosy-lab.org/research/prs/2023-09-13_ASE_CPA-DF_Po-Chun.pdf}, abstract = {Software verification is challenging, and auxiliary program invariants are used to improve the effectiveness of verification approaches. For instance, the <i>k</i>-induction implementation in <a href="https://cpachecker.sosy-lab.org/">CPAchecker</a>, an award-winning framework for program analysis, uses invariants produced by a configurable data-flow analysis to strengthen induction hypotheses. This invariant generator, CPA-DF, uses arithmetic expressions over intervals as its abstract domain and is able to prove some safe verification tasks alone. After extensively evaluating CPA-DF on <a href="https://gitlab.com/sosy-lab/benchmarking/sv-benchmarks">SV-Benchmarks</a>, the largest publicly available suite of C safety-verification tasks, we discover that its potential as a stand-alone analysis or a sub-analysis in a parallel portfolio for combined verification approaches has been significantly underestimated: (1) As a stand-alone analysis, CPA-DF finds almost as many proofs as the plain <i>k</i>-induction implementation without auxiliary invariants. (2) As a sub-analysis running in parallel to the plain <i>k</i>-induction implementation, CPA-DF boosts the portfolio verifier to solve a comparable amount of tasks as the heavily-optimized <i>k</i>-induction implementation with invariant injection. Our detailed analysis reveals that dynamic precision adjustment is crucial to the efficiency and effectiveness of CPA-DF. To generalize our results beyond CPAchecker, we use <a href="https://gitlab.com/sosy-lab/software/coveriteam">CoVeriTeam</a>, a platform for cooperative verification, to compose three portfolio verifiers that execute CPA-DF and three other software verifiers in parallel, respectively. Surprisingly, running CPA-DF merely in parallel to these state-of-the-art tools further boosts the number of correct results up to more than 20&percnt;. <br> Demonstration video: <a href="https://youtu.be/l7UG-vhTL_4">https://youtu.be/l7UG-vhTL_4</a>}, keyword = {Software Model Checking, Cooperative Verification, CPAchecker}, artifact = {10.5281/zenodo.8245821}, funding = {DFG-CONVEY}, video = {https://youtu.be/l7UG-vhTL_4}, }
  14. Dirk Beyer and Martin Spiessl. LIV: Invariant Validation using Straight-Line Programs. In Proc. ASE, pages 2074-2077, 2023. IEEE. doi:10.1109/ASE56229.2023.00214 Link to this entry Keyword(s): Software Model Checking, Witness-Based Validation Funding: DFG-CONVEY Publisher's Version PDF Video Supplement
    Artifact(s)
    Abstract
    Validation of correctness proofs is an established procedure in software verification. While there are steady advances when it comes to verification of more and more complex software systems, it becomes increasingly hard to determine which information is actually useful for validation of the correctness proof. Usually, the central piece that verifiers struggle to come up with are good loop invariants. While a proof using inductive invariants is easy to validate, not all invariants used by verifiers necessarily are inductive. In order to alleviate this problem, we propose LIV, an approach that makes it easy to check if the invariant information provided by the verifier is sufficient to establish an inductive proof. This is done by emulating a Hoare-style proof, splitting the program into Hoare triples and converting these into verification tasks that can themselves be efficiently verified by an off-the-shelf verifier. In case the validation fails, useful information about the failure reason can be extracted from the overview of which triples could be established and which were refuted. We show that our approach works by evaluating it on a state-of-the-art benchmark set.
    BibTeX Entry
    @inproceedings{ASE23b, author = {Dirk Beyer and Martin Spiessl}, title = {{LIV}: {Invariant} Validation using Straight-Line Programs}, booktitle = {Proc.\ ASE}, pages = {2074-2077}, year = {2023}, series = {}, publisher = {IEEE}, doi = {10.1109/ASE56229.2023.00214}, url = {https://www.sosy-lab.org/research/liv}, pdf = {https://www.sosy-lab.org/research/pub/2023-ASE.LIV_Loop-Invariant_Validation_using_Straight-Line_Programs.pdf}, abstract = {Validation of correctness proofs is an established procedure in software verification. While there are steady advances when it comes to verification of more and more complex software systems, it becomes increasingly hard to determine which information is actually useful for validation of the correctness proof. Usually, the central piece that verifiers struggle to come up with are good loop invariants. While a proof using inductive invariants is easy to validate, not all invariants used by verifiers necessarily are inductive. In order to alleviate this problem, we propose LIV, an approach that makes it easy to check if the invariant information provided by the verifier is sufficient to establish an inductive proof. This is done by emulating a Hoare-style proof, splitting the program into Hoare triples and converting these into verification tasks that can themselves be efficiently verified by an off-the-shelf verifier. In case the validation fails, useful information about the failure reason can be extracted from the overview of which triples could be established and which were refuted. We show that our approach works by evaluating it on a state-of-the-art benchmark set.}, keyword = {Software Model Checking, Witness-Based Validation}, artifact = {10.5281/zenodo.8289101}, funding = {DFG-CONVEY}, video = {https://youtu.be/mZhoGAa08Rk}, }
  15. Dirk Beyer, Marian Lingsch-Rosenfeld, and Martin Spiessl. CEGAR-PT: A Tool for Abstraction by Program Transformation. In Proc. ASE, pages 2078-2081, 2023. IEEE. doi:10.1109/ASE56229.2023.00215 Link to this entry Keyword(s): Software Model Checking Funding: DFG-CONVEY Publisher's Version PDF Video Supplement
    Artifact(s)
    Abstract
    Abstraction is a key technology for proving the correctness of computer programs. There are many approaches available, but unfortunately, the various techniques are difficult to combine and the successful techniques have to be re-implemented again and again.
    We address this problem by using the tool CEGAR-PT, which views abstraction as program transformation and integrates different verification components off-the-shelf. The idea is to use existing components without having to change their implementation, while still adjusting the precision of the abstraction using the successful CEGAR approach. The approach is largely general: it only restricts the abstraction to transform, given a precision that defines the level of abstraction, one program into another program. The abstraction by program transformation can over-approximate the data flow (e.g., havoc some variables, use more abstract types) or the control flow (e.g., loop abstraction, slicing).
    BibTeX Entry
    @inproceedings{ASE23c, author = {Dirk Beyer and Marian Lingsch-Rosenfeld and Martin Spiessl}, title = {{CEGAR-PT}: {A} Tool for Abstraction by Program Transformation}, booktitle = {Proc.\ ASE}, pages = {2078-2081}, year = {2023}, series = {}, publisher = {IEEE}, doi = {10.1109/ASE56229.2023.00215}, url = {https://www.sosy-lab.org/research/cegar-pt}, pdf = {https://www.sosy-lab.org/research/pub/2023-ASE.CEGAR-PT_A_Tool_for_Abstraction_by_Program_Transformation.pdf}, abstract = {Abstraction is a key technology for proving the correctness of computer programs. There are many approaches available, but unfortunately, the various techniques are difficult to combine and the successful techniques have to be re-implemented again and again. <br> We address this problem by using the tool CEGAR-PT, which views abstraction as program transformation and integrates different verification components off-the-shelf. The idea is to use existing components without having to change their implementation, while still adjusting the precision of the abstraction using the successful CEGAR approach. The approach is largely general: it only restricts the abstraction to transform, given a precision that defines the level of abstraction, one program into another program. The abstraction by program transformation can over-approximate the data flow (e.g., havoc some variables, use more abstract types) or the control flow (e.g., loop abstraction, slicing).}, keyword = {Software Model Checking}, artifact = {10.5281/zenodo.8287183}, funding = {DFG-CONVEY}, video = {https://youtu.be/ASZ6hoq8asE}, }
  16. Dirk Beyer, Sudeep Kanav, and Henrik Wachowitz. CoVeriTeam Service: Verification as a Service. In Proc. ICSE, pages 21-25, 2023. IEEE. doi:10.1109/ICSE-Companion58688.2023.00017 Link to this entry Keyword(s): Software Model Checking, Incremental Verification, Cooperative Verification Funding: DFG-CONVEY, DFG-COOP Publisher's Version PDF Supplement
    Artifact(s)
    Abstract
    The research community has developed numerous tools for solving verification problems, but we are missing a common interface for executing them. This means users have to spend considerable effort on the installation and parameter setup, for each new tool (version) they want to execute. The situation could make a verification researcher wanting to experiment with a new verification tool turn away from it. We aim to make it easier for users to execute verification tools, as well as provide mechanism for tool developers to make their tools easily accessible. Our solution combines a web service and a common interface for verification tools. The presented service has been used during the 2023 competitions on software verification and testing, for integration testing. As another use- case, we developed a service for incremental verification on top of the CoVeriTeam Service and demonstrate its use in a continuous-integration process.
    BibTeX Entry
    @inproceedings{ICSE23, author = {Dirk Beyer and Sudeep Kanav and Henrik Wachowitz}, title = {{CoVeriTeam Service}: {Verification} as a Service}, booktitle = {Proc.\ ICSE}, pages = {21-25}, year = {2023}, publisher = {IEEE}, doi = {10.1109/ICSE-Companion58688.2023.00017}, url = {https://coveriteam-service.sosy-lab.org/static/index.html}, pdf = {https://www.sosy-lab.org/research/pub/2023-ICSE.CoVeriTeam_Service_Verification_as_a_Service.pdf}, abstract = {The research community has developed numerous tools for solving verification problems, but we are missing a common interface for executing them. This means users have to spend considerable effort on the installation and parameter setup, for each new tool (version) they want to execute. The situation could make a verification researcher wanting to experiment with a new verification tool turn away from it. We aim to make it easier for users to execute verification tools, as well as provide mechanism for tool developers to make their tools easily accessible. Our solution combines a web service and a common interface for verification tools. The presented service has been used during the 2023 competitions on software verification and testing, for integration testing. As another use- case, we developed a service for incremental verification on top of the {CoVeriTeam} Service and demonstrate its use in a continuous-integration process.}, keyword = {Software Model Checking,Incremental Verification,Cooperative Verification}, _sha256 = {604dd391b6a49e46e97b6faafbb3cc331ccf5c04e3d364cf1e76a2c99c1c267f}, artifact = {10.5281/zenodo.7276532}, funding = {DFG-CONVEY,DFG-COOP}, }
  17. Dirk Beyer, Po-Chun Chien, and Nian-Ze Lee. Bridging Hardware and Software Analysis with Btor2C: A Word-Level-Circuit-to-C Translator. In Proc. TACAS, LNCS 13994, pages 152-172, 2023. Springer. doi:10.1007/978-3-031-30820-8_12 Link to this entry Keyword(s): Software Model Checking, Cooperative Verification, Btor2 Funding: DFG-CONVEY Publisher's Version PDF Presentation Supplement
    Artifact(s)
    Abstract
    Across the broad field for the analysis of computational systems, research endeavors are often categorized by the respective models under investigation. Algorithms and tools are usually developed for a specific model, hindering their applications to similar problems originating from other computational systems. A prominent example of such situation is the studies on formal verification and testing for hardware and software systems. The two research communities share common theoretical foundations and solving methods, including satisfiability, interpolation, and abstraction refinement. Nevertheless, it is often demanding for one community to benefit from the advancements of the other, as analyzers typically assume a particular input format. To bridge the gap between the hardware and software analysis, we propose Btor2C, a converter from word-level sequential circuits to C programs. We choose the Btor2 language as the input format for its simplicity and bit-precise semantics. It can be deemed as an intermediate representation tailored for analysis. Given a Btor2 circuit, Btor2C generates a behaviorally equivalent program in the C language, supported by most static program analyzers. We demonstrate the use cases of Btor2C by translating the benchmark set from the Hardware Model Checking Competitions into C programs and analyze them by tools from the Competitions on Software Verification and Testing. Our results show that software analyzers can complement hardware verifiers for enhanced quality assurance.
    BibTeX Entry
    @inproceedings{TACAS23a, author = {Dirk Beyer and Po-Chun Chien and Nian-Ze Lee}, title = {Bridging Hardware and Software Analysis with {Btor2C}: {A} Word-Level-Circuit-to-{C} Translator}, booktitle = {Proc.\ TACAS}, pages = {152-172}, year = {2023}, series = {LNCS~13994}, publisher = {Springer}, doi = {10.1007/978-3-031-30820-8_12}, url = {https://www.sosy-lab.org/research/btor2c/}, presentation = {https://www.sosy-lab.org/research/prs/2023-04-26_TACAS23_Bridging_Hardware_and_Software_Analysis_with_Btor2C_Po-Chun.pdf}, abstract = {Across the broad field for the analysis of computational systems, research endeavors are often categorized by the respective models under investigation. Algorithms and tools are usually developed for a specific model, hindering their applications to similar problems originating from other computational systems. A prominent example of such situation is the studies on formal verification and testing for hardware and software systems. The two research communities share common theoretical foundations and solving methods, including satisfiability, interpolation, and abstraction refinement. Nevertheless, it is often demanding for one community to benefit from the advancements of the other, as analyzers typically assume a particular input format. To bridge the gap between the hardware and software analysis, we propose Btor2C, a converter from word-level sequential circuits to C programs. We choose <a href="https://doi.org/10.1007/978-3-319-96145-3_32">the Btor2 language</a> as the input format for its simplicity and bit-precise semantics. It can be deemed as an intermediate representation tailored for analysis. Given a Btor2 circuit, Btor2C generates a behaviorally equivalent program in the C language, supported by most static program analyzers. We demonstrate the use cases of Btor2C by translating the benchmark set from the Hardware Model Checking Competitions into C programs and analyze them by tools from the Competitions on Software Verification and Testing. Our results show that software analyzers can complement hardware verifiers for enhanced quality assurance.}, keyword = {Software Model Checking, Cooperative Verification, Btor2}, _pdf = {https://www.sosy-lab.org/research/pub/2023-TACAS.Bridging_Hardware_and_Software_Analysis_with_Btor2C_A_Word-Level-Circuit-to-C_Translator.pdf}, artifact = {10.5281/zenodo.7551707}, funding = {DFG-CONVEY}, }
  18. Dirk Beyer, Martin Spiessl, and Sven Umbricht. Cooperation between Automatic and Interactive Software Verifiers. In Bernd-Holger Schlingloff and Ming Chai, editors, Proceedings of the 20th International Conference on Software Engineering and Formal Methods, (SEFM 2022, Berlin, Germany, September 26-30, LNCS 13550, pages 111–128, 2022. Springer. doi:10.1007/978-3-031-17108-6_7 Link to this entry Keyword(s): Software Model Checking, CPAchecker Funding: DFG-CONVEY Publisher's Version PDF
    BibTeX Entry
    @inproceedings{SEFM22b, author = {Dirk Beyer and Martin Spiessl and Sven Umbricht}, title = {Cooperation between Automatic and Interactive Software Verifiers}, booktitle = {Proceedings of the 20th International Conference on Software Engineering and Formal Methods, (SEFM~2022, Berlin, Germany, September 26-30}, editor = {Bernd-Holger Schlingloff and Ming Chai}, pages = {111–128}, year = {2022}, series = {LNCS~13550}, publisher = {Springer}, doi = {10.1007/978-3-031-17108-6_7}, sha256 = {a310ff0ac97f37ee817c6f05a4cc9a635cbacd09ad301b483095f133040e8e48}, url = {}, abstract = {}, keyword = {Software Model Checking, CPAchecker}, _pdf = {https://www.sosy-lab.org/research/pub/2022-SEFM.Cooperation_between_Automatic_and_Interactive_Software_Verifiers.pdf}, funding = {DFG-CONVEY}, }
  19. Dirk Beyer, Marian Lingsch Rosenfeld, and Martin Spiessl. A Unifying Approach for Control-Flow-Based Loop Abstraction. In Bernd-Holger Schlingloff and Ming Chai, editors, Proceedings of the 20th International Conference on Software Engineering and Formal Methods, (SEFM 2022, Berlin, Germany, September 26-30, LNCS 13550, pages 3-19, 2022. Springer. doi:10.1007/978-3-031-17108-6_1 Link to this entry Keyword(s): Software Model Checking, CPAchecker Funding: DFG-CONVEY Publisher's Version PDF
    BibTeX Entry
    @inproceedings{SEFM22a, author = {Dirk Beyer and Marian Lingsch Rosenfeld and Martin Spiessl}, title = {A Unifying Approach for Control-Flow-Based Loop Abstraction}, booktitle = {Proceedings of the 20th International Conference on Software Engineering and Formal Methods, (SEFM~2022, Berlin, Germany, September 26-30}, editor = {Bernd-Holger Schlingloff and Ming Chai}, pages = {3-19}, year = {2022}, series = {LNCS~13550}, publisher = {Springer}, doi = {10.1007/978-3-031-17108-6_1}, sha256 = {047a8a9062e143741623320cf80ec963ce5f7200a5a75d263fa6615c12f2199e}, url = {}, abstract = {}, keyword = {Software Model Checking, CPAchecker}, _pdf = {https://www.sosy-lab.org/research/pub/2022-SEFM.A_Unifying_Approach_for_Control-Flow-Based_Loop_Abstraction.pdf}, funding = {DFG-CONVEY}, }
  20. Dirk Beyer and Martin Spiessl. The Static Analyzer Frama-C in SV-COMP (Competition Contribution). In Dana Fisman and Grigore Rosu, editors, Proceedings of the 28th International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS 2022, Munich, Germany, April 2-7, LNCS 13244, pages 429-434, 2022. Springer. doi:10.1007/978-3-030-99527-0_26 Link to this entry Keyword(s): Competition on Software Verification (SV-COMP), Software Model Checking Funding: DFG-CONVEY Publisher's Version PDF
    BibTeX Entry
    @inproceedings{TACAS22c, author = {Dirk Beyer and Martin Spiessl}, title = {The Static Analyzer {Frama-C} in {SV-COMP} (Competition Contribution)}, booktitle = {Proceedings of the 28th International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS~2022, Munich, Germany, April 2-7}, editor = {Dana Fisman and Grigore Rosu}, pages = {429--434}, year = {2022}, series = {LNCS~13244}, publisher = {Springer}, doi = {10.1007/978-3-030-99527-0_26}, sha256 = {77ed425c2b30a4f9424ed46c9cb5a846f5c21677ececdbf098e30f37aca67a3d}, url = {}, abstract = {}, keyword = {Competition on Software Verification (SV-COMP),Software Model Checking}, _pdf = {https://www.sosy-lab.org/research/pub/2022-TACAS.The_Static_Analyzer_Frama-C_in_SV-COMP_Competition_Contribution.pdf}, funding = {DFG-CONVEY}, }
  21. Dirk Beyer, Karlheinz Friedberger, and Stephan Holzner. PJBDD: A BDD Library for Java and Multi-Threading. In Proceedings of the 19th International Symposium on Automated Technology for Verification and Analysis (ATVA21 2021, Gold Coast (Online), Australia, October 18-22), 2021. Springer. doi:10.1007/978-3-030-88885-5_10 Link to this entry Keyword(s): PJBDD, BDD Funding: DFG-CONVEY Publisher's Version PDF
    Artifact(s)
    Abstract
    PJBDD is a flexible and modular Java library for binary decision diagrams (BDD), which are a well-known data structure for performing efficient operations on compressed sets and relations. BDDs have practical applications in composing and analyzing boolean functions, e.g., for computer-aided verification. Despite its importance, there are only a few BDD libraries available. PJBDD is based on a slim object-oriented design, supports multi-threaded execution of the BDD operations (internal) as well as thread-safe access to the operations from applications (external). It provides automatic reference counting and garbage collection. The modular design of the library allows us to provide a uniform API for binary decision diagrams, zero-suppressed decision diagrams, and also chained decision diagrams. This paper includes a compact evaluation of PJBDD, to demonstrate that concurrent operations on large BDDs scale well and parallelize nicely on multi-core CPUs.
    BibTeX Entry
    @inproceedings{ATVA21, author = {Dirk Beyer and Karlheinz Friedberger and Stephan Holzner}, title = {{PJBDD}: {A} {BDD} Library for {Java} and Multi-Threading}, booktitle = {Proceedings of the 19th International Symposium on Automated Technology for Verification and Analysis (ATVA21~2021, Gold Coast (Online), Australia, October 18-22)}, year = {2021}, publisher = {Springer}, doi = {10.1007/978-3-030-88885-5_10}, pdf = {https://www.sosy-lab.org/research/pub/2021-ATVA.PJBDD_A_BDD_Library_for_Java_and_Multi_Threading.pdf}, abstract = {PJBDD is a flexible and modular Java library for binary decision diagrams (BDD), which are a well-known data structure for performing efficient operations on compressed sets and relations. BDDs have practical applications in composing and analyzing boolean functions, e.g., for computer-aided verification. Despite its importance, there are only a few BDD libraries available. PJBDD is based on a slim object-oriented design, supports multi-threaded execution of the BDD operations (internal) as well as thread-safe access to the operations from applications (external). It provides automatic reference counting and garbage collection. The modular design of the library allows us to provide a uniform API for binary decision diagrams, zero-suppressed decision diagrams, and also chained decision diagrams. This paper includes a compact evaluation of PJBDD, to demonstrate that concurrent operations on large BDDs scale well and parallelize nicely on multi-core CPUs.}, keyword = {PJBDD,BDD}, artifact = {10.5281/zenodo.5070156}, funding = {DFG-CONVEY}, }
  22. Daniel Baier, Dirk Beyer, and Karlheinz Friedberger. JavaSMT 3: Interacting with SMT Solvers in Java. In A. Silva and K. R. M. Leino, editors, Proceedings of the 33rd International Conference on Computer-Aided Verification (CAV 2021, Los Angeles, California, USA, July 18-24), LNCS 12760, pages 1-13, 2021. Springer. doi:10.1007/978-3-030-81688-9_9 Link to this entry Keyword(s): JavaSMT Funding: DFG-CONVEY Publisher's Version PDF Supplement
    BibTeX Entry
    @inproceedings{CAV21, author = {Daniel Baier and Dirk Beyer and Karlheinz Friedberger}, title = {JavaSMT 3: Interacting with SMT Solvers in Java}, booktitle = {Proceedings of the 33rd International Conference on Computer-Aided Verification (CAV~2021, Los Angeles, California, USA, July 18-24)}, editor = {A.~Silva and K.~R.~M.~Leino}, pages = {1-13}, year = {2021}, series = {LNCS~12760}, publisher = {Springer}, doi = {10.1007/978-3-030-81688-9_9}, sha256 = {6c0ff13c5dd8596e19be4176eefaafe5853d60a082b78ebd3f5e64381fdcb100}, url = {https://github.com/sosy-lab/java-smt}, abstract = {}, keyword = {JavaSMT}, _pdf = {https://www.sosy-lab.org/research/pub/2021-CAV.JavaSMT_3_Interacting_with_SMT_Solvers_in_Java.pdf}, funding = {DFG-CONVEY}, }
  23. Dirk Beyer. Software Verification: 10th Comparative Evaluation (SV-COMP 2021). In J. F. Groote and K. G. Larsen, editors, Proceedings of the 27th International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS 2021, Luxembourg, Luxembourg, March 27 - April 1), part 2, LNCS 12652, pages 401-422, 2021. Springer. doi:10.1007/978-3-030-72013-1_24 Link to this entry Keyword(s): Competition on Software Verification (SV-COMP), Competition on Software Verification (SV-COMP Report), Software Model Checking Funding: DFG-CONVEY Publisher's Version PDF Supplement
    BibTeX Entry
    @inproceedings{TACAS21, author = {Dirk Beyer}, title = {Software Verification: 10th Comparative Evaluation ({SV-COMP 2021})}, booktitle = {Proceedings of the 27th International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS~2021, Luxembourg, Luxembourg, March 27 - April 1), part 2}, editor = {J.~F.~Groote and K.~G.~Larsen}, pages = {401-422}, year = {2021}, series = {LNCS~12652}, publisher = {Springer}, doi = {10.1007/978-3-030-72013-1_24}, sha256 = {d78bb586715b0650702665510258d8e53a7bd16ae2a3cc4568b5986527b29051}, url = {https://sv-comp.sosy-lab.org/2021/}, abstract = {}, keyword = {Competition on Software Verification (SV-COMP),Competition on Software Verification (SV-COMP Report),Software Model Checking}, funding = {DFG-CONVEY}, }
  24. Dirk Beyer and Karlheinz Friedberger. Domain-Independent Interprocedural Program Analysis using Block-Abstraction Memoization. In P. Devanbu, M. Cohen, and T. Zimmermann, editors, Proceedings of the 28th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2020, Virtual Event, USA, November 8-13), pages 50-62, 2020. ACM. doi:10.1145/3368089.3409718 Link to this entry Keyword(s): CPAchecker, Software Model Checking Funding: DFG-CONVEY Publisher's Version PDF Supplement
    Artifact(s)
    BibTeX Entry
    @inproceedings{FSE20, author = {Dirk Beyer and Karlheinz Friedberger}, title = {Domain-Independent Interprocedural Program Analysis using Block-Abstraction Memoization}, booktitle = {Proceedings of the 28th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE~2020, Virtual Event, USA, November 8-13)}, editor = {P.~Devanbu and M.~Cohen and T.~Zimmermann}, pages = {50-62}, year = {2020}, publisher = {ACM}, doi = {10.1145/3368089.3409718}, url = {https://cpachecker.sosy-lab.org}, keyword = {CPAchecker,Software Model Checking}, _sha256 = {36dc2a423425ee8bec03f0f4073e04f9121d299cc475e27190828e8276e00cb8}, artifact = {10.5281/zenodo.4024268}, funding = {DFG-CONVEY}, fundingid = {378803395}, }
  25. Dirk Beyer and Karlheinz Friedberger. Violation Witnesses and Result Validation for Multi-Threaded Programs. In T. Margaria and B. Steffen, editors, Proceedings of the 9th International Symposium on Leveraging Applications of Formal Methods, Verification, and Validation (ISoLA 2020, Rhodos, Greece, October 26-30), part 1, LNCS 12476, pages 449-470, 2020. Springer. doi:10.1007/978-3-030-61362-4_26 Link to this entry Keyword(s): CPAchecker, Software Model Checking, Witness-Based Validation, Witness-Based Validation (main) Funding: DFG-CONVEY Publisher's Version PDF Presentation Supplement
    BibTeX Entry
    @inproceedings{ISoLA20c, author = {Dirk Beyer and Karlheinz Friedberger}, title = {Violation Witnesses and Result Validation for Multi-Threaded Programs}, booktitle = {Proceedings of the 9th International Symposium on Leveraging Applications of Formal Methods, Verification, and Validation (ISoLA~2020, Rhodos, Greece, October 26-30), part~1}, editor = {T.~Margaria and B.~Steffen}, pages = {449-470}, year = {2020}, series = {LNCS~12476}, publisher = {Springer}, doi = {10.1007/978-3-030-61362-4_26}, sha256 = {65fc5325c4e77a80d8e47f9c0e7f0ac02379bfa15dcd9fb54d6587185b8efd77}, url = {https://www.sosy-lab.org/research/witnesses-concurrency/}, presentation = {https://www.sosy-lab.org/research/prs/2021-10-25_ISOLA21_ValidationMultiThreaded_Dirk.pdf}, abstract = {}, keyword = {CPAchecker,Software Model Checking,Witness-Based Validation,Witness-Based Validation (main)}, funding = {DFG-CONVEY}, }
  26. Dirk Beyer and Sudeep Kanav. An Interface Theory for Program Verification. In T. Margaria and B. Steffen, editors, Proceedings of the 9th International Symposium on Leveraging Applications of Formal Methods, Verification, and Validation (ISoLA 2020, Rhodos, Greece, October 26-30), part 1, LNCS 12476, pages 168-186, 2020. Springer. doi:10.1007/978-3-030-61362-4_9 Link to this entry Keyword(s): CPAchecker, Software Model Checking, Interfaces for Component-Based Design Funding: DFG-CONVEY Publisher's Version PDF Presentation
    BibTeX Entry
    @inproceedings{ISoLA20b, author = {Dirk Beyer and Sudeep Kanav}, title = {An Interface Theory for Program Verification}, booktitle = {Proceedings of the 9th International Symposium on Leveraging Applications of Formal Methods, Verification, and Validation (ISoLA~2020, Rhodos, Greece, October 26-30), part~1}, editor = {T.~Margaria and B.~Steffen}, pages = {168-186}, year = {2020}, series = {LNCS~12476}, publisher = {Springer}, doi = {10.1007/978-3-030-61362-4_9}, sha256 = {f15159da0e648a25e57c769639c989e68cd3407bfad10db5ee1dc25e1d2fd672}, url = {}, presentation = {https://www.sosy-lab.org/research/prs/2021-10-29_ISOLA21_VerificationInterfaces_Dirk.pdf}, abstract = {}, keyword = {CPAchecker,Software Model Checking,Interfaces for Component-Based Design}, funding = {DFG-CONVEY}, }
  27. Dirk Beyer, Marie-Christine Jakobs, and Thomas Lemberger. Difference Verification with Conditions. In F. d. Boer and A. Cerone, editors, Proceedings of the 18th International Conference on Software Engineering and Formal Methods (SEFM 2020, Virtual, Netherlands, September 14-18), LNCS 12310, pages 133-154, 2020. Springer. doi:10.1007/978-3-030-58768-0_8 Link to this entry Keyword(s): CPAchecker, Software Model Checking Funding: DFG-COOP, DFG-CONVEY Publisher's Version PDF Presentation Video Supplement
    Abstract
    Modern software-verification tools need to support development processes that involve frequent changes. Existing approaches for incremental verification hard-code specific verification techniques. Some of the approaches must be tightly intertwined with the development process. To solve this open problem, we present the concept of difference verification with conditions. Difference verification with conditions is independent from any specific verification technique and can be integrated in software projects at any time. It first applies a change analysis that detects which parts of a software were changed between revisions and encodes that information in a condition. Based on this condition, an off-the-shelf verifier is used to verify only those parts of the software that are influenced by the changes. As a proof of concept, we propose a simple, syntax-based change analysis and use difference verification with conditions with three off-the-shelf verifiers. An extensive evaluation shows the competitiveness of difference verification with conditions.
    BibTeX Entry
    @inproceedings{SEFM20b, author = {Dirk Beyer and Marie-Christine Jakobs and Thomas Lemberger}, title = {Difference Verification with Conditions}, booktitle = {Proceedings of the 18th International Conference on Software Engineering and Formal Methods (SEFM~2020, Virtual, Netherlands, September 14-18)}, editor = {F.~d.~Boer and A.~Cerone}, pages = {133--154}, year = {2020}, series = {LNCS~12310}, publisher = {Springer}, doi = {10.1007/978-3-030-58768-0_8}, sha256 = {8e5219da9a998b26f59013c809fbb1db6f92e3f08125fa1bfaacafcfafafef7f}, url = {https://www.sosy-lab.org/research/difference/}, presentation = {https://www.sosy-lab.org/research/prs/2020-09-17_SEFM20_DifferenceVerificationWithConditions_Thomas.pdf}, abstract = {Modern software-verification tools need to support development processes that involve frequent changes. Existing approaches for incremental verification hard-code specific verification techniques. Some of the approaches must be tightly intertwined with the development process. To solve this open problem, we present the concept of difference verification with conditions. Difference verification with conditions is independent from any specific verification technique and can be integrated in software projects at any time. It first applies a change analysis that detects which parts of a software were changed between revisions and encodes that information in a condition. Based on this condition, an off-the-shelf verifier is used to verify only those parts of the software that are influenced by the changes. As a proof of concept, we propose a simple, syntax-based change analysis and use difference verification with conditions with three off-the-shelf verifiers. An extensive evaluation shows the competitiveness of difference verification with conditions.}, keyword = {CPAchecker,Software Model Checking}, funding = {DFG-COOP,DFG-CONVEY}, isbnnote = {}, video = {https://youtu.be/dG02602c9oo}, }
  28. Dirk Beyer and Martin Spiessl. MetaVal: Witness Validation via Verification. In S. K. Lahiri and C. Wang, editors, Proceedings of the 32nd International Conference on Computer Aided Verification (CAV 2020, Virtual, USA, July 21-24), part 2, LNCS 12225, pages 165-177, 2020. Springer. doi:10.1007/978-3-030-53291-8_10 Link to this entry Keyword(s): CPAchecker, Software Model Checking, Witness-Based Validation, Witness-Based Validation (main) Funding: DFG-CONVEY Publisher's Version PDF Supplement
    BibTeX Entry
    @inproceedings{CAV20, author = {Dirk Beyer and Martin Spiessl}, title = {MetaVal: {W}itness Validation via Verification}, booktitle = {Proceedings of the 32nd International Conference on Computer Aided Verification (CAV~2020, Virtual, USA, July 21-24), part 2}, editor = {S.~K.~Lahiri and C.~Wang}, pages = {165-177}, year = {2020}, series = {LNCS~12225}, publisher = {Springer}, doi = {10.1007/978-3-030-53291-8_10}, sha256 = {7431085a248c7e2cab70318096622ff19ce1124067158d08866d3f9b250df44e}, url = {https://gitlab.com/sosy-lab/software/metaval}, abstract = {}, keyword = {CPAchecker,Software Model Checking,Witness-Based Validation,Witness-Based Validation (main)}, funding = {DFG-CONVEY}, isbnnote = {978-3-030-53290-1}, }

Internal reports

  1. Daniel Baier, Dirk Beyer, Po-Chun Chien, Marie-Christine Jakobs, Marek Jankola, Matthias Kettl, Nian-Ze Lee, Thomas Lemberger, Marian Lingsch-Rosenfeld, Henrik Wachowitz, and Philipp Wendler. Software Verification with CPAchecker 3.0: Tutorial and User Guide (Extended Version). Technical report 2409.02094, arXiv/CoRR, September 2024. doi:10.48550/arXiv.2409.02094 Link to this entry Keyword(s): CPAchecker, Software Model Checking, Software Testing Funding: DFG-COOP, DFG-CONVEY, DFG-IDEFIX Publisher's Version PDF Presentation Supplement
    Artifact(s)
    Abstract
    This tutorial provides an introduction to CPAchecker for users. CPAchecker is a flexible and configurable framework for software verification and testing. The framework provides many abstract domains, such as BDDs, explicit values, intervals, memory graphs, and predicates, and many program-analysis and model-checking algorithms, such as abstract interpretation, bounded model checking, Impact, interpolation-based model checking, k-induction, PDR, predicate abstraction, and symbolic execution. This tutorial presents basic use cases for CPAchecker in formal software verification, focusing on its main verification techniques with their strengths and weaknesses. It also shows further use cases of CPAchecker for test-case generation and witness-based result validation. The envisioned readers are assumed to possess a background in automatic formal verification and program analysis, but prior knowledge of CPAchecker is not required. This tutorial and user guide is based on CPAchecker in version 3.0. This user guide's latest version and other documentation are available at https://cpachecker.sosy-lab.org/doc.php.
    BibTeX Entry
    @techreport{TechReport24c, author = {Daniel Baier and Dirk Beyer and Po-Chun Chien and Marie-Christine Jakobs and Marek Jankola and Matthias Kettl and Nian-Ze Lee and Thomas Lemberger and Marian Lingsch-Rosenfeld and Henrik Wachowitz and Philipp Wendler}, title = {Software Verification with {CPAchecker} 3.0: {Tutorial} and User Guide (Extended Version)}, number = {2409.02094}, year = {2024}, doi = {10.48550/arXiv.2409.02094}, url = {https://cpachecker.sosy-lab.org}, presentation = {https://www.sosy-lab.org/research/prs/2024-09-10_FM24_CPAchecker_Tutorial.pdf}, abstract = {This tutorial provides an introduction to CPAchecker for users. CPAchecker is a flexible and configurable framework for software verification and testing. The framework provides many abstract domains, such as BDDs, explicit values, intervals, memory graphs, and predicates, and many program-analysis and model-checking algorithms, such as abstract interpretation, bounded model checking, Impact, interpolation-based model checking, <i>k</i>-induction, PDR, predicate abstraction, and symbolic execution. This tutorial presents basic use cases for CPAchecker in formal software verification, focusing on its main verification techniques with their strengths and weaknesses. It also shows further use cases of CPAchecker for test-case generation and witness-based result validation. The envisioned readers are assumed to possess a background in automatic formal verification and program analysis, but prior knowledge of CPAchecker is not required. This tutorial and user guide is based on CPAchecker in version 3.0. This user guide's latest version and other documentation are available at <a href="https://cpachecker.sosy-lab.org/doc.php">https://cpachecker.sosy-lab.org/doc.php</a>.}, keyword = {CPAchecker, Software Model Checking, Software Testing}, annote = {This technical report is an extended version of our <a href="https://www.sosy-lab.org/research/bib/All/index.html#FM24a">paper</a> at FM 2024.}, artifact = {10.5281/zenodo.13612338}, funding = {DFG-COOP, DFG-CONVEY, DFG-IDEFIX}, institution = {arXiv/CoRR}, month = {September}, }
    Additional Infos
    This technical report is an extended version of our paper at FM 2024.
  2. Salih Ates, Dirk Beyer, Po-Chun Chien, and Nian-Ze Lee. MoXIchecker: An Extensible Model Checker for MoXI. Technical report 2407.15551, arXiv/CoRR, March 2024. doi:10.48550/arXiv.2407.15551 Link to this entry Keyword(s): Btor2 Funding: DFG-CONVEY, DFG-BRIDGE Publisher's Version PDF Supplement
    Artifact(s)
    Abstract
    MoXI is a new intermediate verification language introduced in 2024 to promote the standardization and open-source implementations for symbolic model checking by extending the SMT-LIB 2 language with constructs to define state-transition systems. The tool suite of MoXI provides a translator from MoXI to Btor2, which is a lower-level intermediate language for hardware verification, and a translation-based model checker, which invokes mature hardware model checkers for Btor2 to analyze the translated verification tasks. The extensibility of such a translation-based model checker is restricted because more complex theories, such as integer or real arithmetics, cannot be precisely expressed with bit-vectors of fixed lengths in Btor2. We present MoXIchecker, the first model checker that solves MoXI verification tasks directly. Instead of translating MoXI to lower-level languages, MoXIchecker uses the solver-agnostic library PySMT for SMT solvers as backend for its verification algorithms. MoXIchecker is extensible because it accommodates verification tasks involving more complex theories, not limited by lower-level languages, facilitates the implementation of new algorithms, and is solver-agnostic by using the API of PySMT. In our evaluation, MoXIchecker uniquely solved tasks that use integer or real arithmetics, and achieved a comparable performance against the translation-based model checker from the MoXI tool suite.
    BibTeX Entry
    @techreport{TechReport24b, author = {Salih Ates and Dirk Beyer and Po-Chun Chien and Nian-Ze Lee}, title = {{MoXIchecker}: {An} Extensible Model Checker for {MoXI}}, number = {2407.15551}, year = {2024}, doi = {10.48550/arXiv.2407.15551}, url = {https://gitlab.com/sosy-lab/software/moxichecker}, pdf = {https://arxiv.org/abs/2407.15551}, abstract = {MoXI is a new intermediate verification language introduced in 2024 to promote the standardization and open-source implementations for symbolic model checking by extending the SMT-LIB 2 language with constructs to define state-transition systems. The tool suite of MoXI provides a translator from MoXI to Btor2, which is a lower-level intermediate language for hardware verification, and a translation-based model checker, which invokes mature hardware model checkers for Btor2 to analyze the translated verification tasks. The extensibility of such a translation-based model checker is restricted because more complex theories, such as integer or real arithmetics, cannot be precisely expressed with bit-vectors of fixed lengths in Btor2. We present MoXIchecker, the first model checker that solves MoXI verification tasks directly. Instead of translating MoXI to lower-level languages, MoXIchecker uses the solver-agnostic library PySMT for SMT solvers as backend for its verification algorithms. MoXIchecker is extensible because it accommodates verification tasks involving more complex theories, not limited by lower-level languages, facilitates the implementation of new algorithms, and is solver-agnostic by using the API of PySMT. In our evaluation, MoXIchecker uniquely solved tasks that use integer or real arithmetics, and achieved a comparable performance against the translation-based model checker from the MoXI tool suite.}, keyword = {Btor2}, artifact = {10.5281/zenodo.12787654}, funding = {DFG-CONVEY,DFG-BRIDGE}, institution = {arXiv/CoRR}, month = {March}, }
  3. Dirk Beyer, Po-Chun Chien, and Nian-Ze Lee. Augmenting Interpolation-Based Model Checking with Auxiliary Invariants (Extended Version). Technical report 2403.07821, arXiv/CoRR, March 2024. doi:10.48550/arXiv.2403.07821 Link to this entry Keyword(s): Software Model Checking, Cooperative Verification, CPAchecker Funding: DFG-CONVEY Publisher's Version PDF Supplement
    Artifact(s)
    Abstract
    Software model checking is a challenging problem, and generating relevant invariants is a key factor in proving the safety properties of a program. Program invariants can be obtained by various approaches, including lightweight procedures based on data-flow analysis and intensive techniques using Craig interpolation. Although data-flow analysis runs efficiently, it often produces invariants that are too weak to prove the properties. By contrast, interpolation-based approaches build strong invariants from interpolants, but they might not scale well due to expensive interpolation procedures. Invariants can also be injected into model-checking algorithms to assist the analysis. Invariant injection has been studied for many well-known approaches, including k-induction, predicate abstraction, and symbolic execution. We propose an augmented interpolation-based verification algorithm that injects external invariants into interpolation-based model checking (McMillan, 2003), a hardware model-checking algorithm recently adopted for software verification. The auxiliary invariants help prune unreachable states in Craig interpolants and confine the analysis to the reachable parts of a program. We implemented the proposed technique in the verification framework CPAchecker and evaluated it against mature SMT-based methods in CPAchecker as well as other state-of-the-art software verifiers. We found that injecting invariants reduces the number of interpolation queries needed to prove safety properties and improves the run-time efficiency. Consequently, the proposed invariant-injection approach verified difficult tasks that none of its plain version (i.e., without invariants), the invariant generator, or any compared tools could solve.
    BibTeX Entry
    @techreport{TechReport24a, author = {Dirk Beyer and Po-Chun Chien and Nian-Ze Lee}, title = {Augmenting Interpolation-Based Model Checking with Auxiliary Invariants (Extended Version)}, number = {2403.07821}, year = {2024}, doi = {10.48550/arXiv.2403.07821}, url = {https://www.sosy-lab.org/research/imc-df/}, pdf = {https://arxiv.org/abs/2403.07821}, abstract = {Software model checking is a challenging problem, and generating relevant invariants is a key factor in proving the safety properties of a program. Program invariants can be obtained by various approaches, including lightweight procedures based on data-flow analysis and intensive techniques using Craig interpolation. Although data-flow analysis runs efficiently, it often produces invariants that are too weak to prove the properties. By contrast, interpolation-based approaches build strong invariants from interpolants, but they might not scale well due to expensive interpolation procedures. Invariants can also be injected into model-checking algorithms to assist the analysis. Invariant injection has been studied for many well-known approaches, including <i>k</i>-induction, predicate abstraction, and symbolic execution. We propose an augmented interpolation-based verification algorithm that injects external invariants into interpolation-based model checking (McMillan, 2003), a hardware model-checking algorithm recently adopted for software verification. The auxiliary invariants help prune unreachable states in Craig interpolants and confine the analysis to the reachable parts of a program. We implemented the proposed technique in the verification framework CPAchecker and evaluated it against mature SMT-based methods in CPAchecker as well as other state-of-the-art software verifiers. We found that injecting invariants reduces the number of interpolation queries needed to prove safety properties and improves the run-time efficiency. Consequently, the proposed invariant-injection approach verified difficult tasks that none of its plain version (i.e., without invariants), the invariant generator, or any compared tools could solve.}, keyword = {Software Model Checking, Cooperative Verification, CPAchecker}, annote = {This technical report is an extended version of our <a href="https://www.sosy-lab.org/research/bib/All/index.html#SPIN24b">paper</a> at SPIN 2024.}, artifact = {10.5281/zenodo.10548594}, funding = {DFG-CONVEY}, institution = {arXiv/CoRR}, month = {March}, }
    Additional Infos
    This technical report is an extended version of our paper at SPIN 2024.
  4. Po-Chun Chien. Bridging Hardware and Software Formal Verification (Extended Abstract). Technical report 2024-06, LMU Munich, 2024. Link to this entry Keyword(s): Software Model Checking, Cooperative Verification, Btor2, CPAchecker, Witness-Based Validation Funding: DFG-CONVEY PDF
    Abstract
    Modern technology relies heavily on the integration of hardware and software systems, from embedded devices in consumer electronics to safety-critical controllers. Despite their interdependence, the tools and methods used for verifying the correctness and reliability of these systems are often segregated, meaning that the advancement in one community cannot benefit another directly. Addressing this challenge, my dissertation aims at bridging the gap between hardware and software formal analysis. This involves translating representations of verification tasks, generating certificates for verification results, integrating state-of-the-art formal analysis tools into a cohesive framework, and adapting and combining model-checking algorithms across domains. By translating word-level hardware circuits into C programs, we found out that software analyzers were able to identify property violations that well-established hardware verifiers failed to detect. Moreover, by adopting interpolation-based hardware-verification algorithms for software analysis, we were able to tackle tasks unsolvable by existing methods. Our research consolidates knowledge from both hardware and software domains, paving a pathway for comprehensive system-level verification.
    BibTeX Entry
    @techreport{chien:fm24-doc-symposium, author = {Po-Chun Chien}, title = {Bridging Hardware and Software Formal Verification (Extended Abstract)}, number = {2024-06}, year = {2024}, pdf = {https://www.sosy-lab.org/research/pub/2024-FM_Doctoral_Symposium.Bridging_Hardware_and_Software_Formal_Verification_Extended_Abstract.pdf}, abstract = {Modern technology relies heavily on the integration of hardware and software systems, from embedded devices in consumer electronics to safety-critical controllers. Despite their interdependence, the tools and methods used for verifying the correctness and reliability of these systems are often segregated, meaning that the advancement in one community cannot benefit another directly. Addressing this challenge, my dissertation aims at bridging the gap between hardware and software formal analysis. This involves translating representations of verification tasks, generating certificates for verification results, integrating state-of-the-art formal analysis tools into a cohesive framework, and adapting and combining model-checking algorithms across domains. By translating word-level hardware circuits into C programs, we found out that software analyzers were able to identify property violations that well-established hardware verifiers failed to detect. Moreover, by adopting interpolation-based hardware-verification algorithms for software analysis, we were able to tackle tasks unsolvable by existing methods. Our research consolidates knowledge from both hardware and software domains, paving a pathway for comprehensive system-level verification.}, keyword = {Software Model Checking, Cooperative Verification, Btor2, CPAchecker, Witness-Based Validation}, annote = {An extended abstract of the dissertation project. Submitted to the Doctoral Symposium of FM 2024.}, funding = {DFG-CONVEY}, institution = {LMU Munich}, }
    Additional Infos
    An extended abstract of the dissertation project. Submitted to the Doctoral Symposium of FM 2024.

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