Software and Computational Systems Lab

Publications of Matthias Kettl

1. 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 Keyword(s): CPAchecker, Software Model Checking Funding: DFG-CONVEY, DFG-COOP Publisher's Version PDF Supplement
   Artifact(s)

   1. doi:10.5281/zenodo.11095864
   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}, }

2. 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 Keyword(s): CPAchecker, Software Model Checking, Software Testing Funding: DFG-COOP, DFG-CONVEY, DFG-IDEFIX Publisher's Version PDF Presentation Supplement
   Artifact(s)

   1. doi:10.5281/zenodo.13612338
   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.
3. Dirk Beyer, Lars Grunske, Matthias Kettl, Marian Lingsch-Rosenfeld, and Moeketsi Raselimo. P3: A Dataset of Partial Program Patches. In Proc. MSR, 2024. ACM. doi:10.1145/3643991.3644889 Keyword(s): Partial Fix, Dataset, Mining Funding: DFG-IDEFIX Publisher's Version PDF Supplement
   Artifact(s)

   1. doi:10.5281/zenodo.10319627
   Abstract

   Identifying and fixing bugs in programs remains a challenge and is one of the most time-consuming tasks in software development. But even after a bug is identified, and a fix has been proposed by a developer or tool, it is not uncommon that the fix is incomplete and does not cover all possible inputs that trigger the bug. This can happen quite often and leads to re-opened issues and inefficiencies. In this paper, we introduce P3, a curated dataset composed of in- complete fixes. Each entry in the set contains a series of commits fixing the same underlying issue, where multiple of the intermediate commits are incomplete fixes. These are sourced from real-world open-source C projects. The selection process involves both auto- mated and manual stages. Initially, we employ heuristics to identify potential partial fixes from repositories, subsequently we validate them through meticulous manual inspection. This process ensures the accuracy and reliability of our curated dataset. We envision that the dataset will support researchers while investigating par- tial fixes in more detail, allowing them to develop new techniques to detect and fix them.
   BibTeX Entry

   @inproceedings{MSR24, author = {Dirk Beyer and Lars Grunske and Matthias Kettl and Marian Lingsch-Rosenfeld and Moeketsi Raselimo}, title = {P3: A Dataset of Partial Program Patches}, booktitle = {Proc.\ MSR}, pages = {}, year = {2024}, publisher = {ACM}, doi = {10.1145/3643991.3644889}, url = {https://gitlab.com/sosy-lab/research/data/partial-fix-dataset}, pdf = {}, abstract = {Identifying and fixing bugs in programs remains a challenge and is one of the most time-consuming tasks in software development. But even after a bug is identified, and a fix has been proposed by a developer or tool, it is not uncommon that the fix is incomplete and does not cover all possible inputs that trigger the bug. This can happen quite often and leads to re-opened issues and inefficiencies. In this paper, we introduce P3, a curated dataset composed of in- complete fixes. Each entry in the set contains a series of commits fixing the same underlying issue, where multiple of the intermediate commits are incomplete fixes. These are sourced from real-world open-source C projects. The selection process involves both auto- mated and manual stages. Initially, we employ heuristics to identify potential partial fixes from repositories, subsequently we validate them through meticulous manual inspection. This process ensures the accuracy and reliability of our curated dataset. We envision that the dataset will support researchers while investigating par- tial fixes in more detail, allowing them to develop new techniques to detect and fix them.}, keyword = {Partial Fix, Dataset, Mining}, annote = {}, artifact = {10.5281/zenodo.10319627}, funding = {DFG-IDEFIX}, }
4. 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 Keyword(s): Software Model Checking, Witness-Based Validation, CPAchecker Funding: DFG-CONVEY, DFG-IDEFIX, DFG-COOP Publisher's Version PDF
   Artifact(s)

   1. doi:10.5281/zenodo.10794627
   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.
5. 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 Keyword(s): Software Model Checking, Witness-Based Validation, CPAchecker Funding: DFG-CONVEY, DFG-IDEFIX Publisher's Version PDF Supplement
   Artifact(s)

   1. doi:10.5281/zenodo.10203297
   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}, }
6. Matthias Kettl and Thomas Lemberger. The Static Analyzer Infer 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), Part 2, LNCS 13244, pages 451-456, 2022. Springer. doi:10.1007/978-3-030-99527-0_30 Keyword(s): Competition on Software Verification (SV-COMP) Publisher's Version PDF Presentation
   Abstract

   We present Infer-SV, a wrapper that adapts Infer for SV-COMP. Infer is a static-analysis tool for C and other languages, developed by Facebook and used by multiple large companies. It is strongly aimed at industry and the internal use at Facebook. Despite its popularity, there are no reported numbers on its precision and efficiency. With Infer-SV, we take a first step towards an objective comparison of Infer with other SV-COMP participants from academia and industry.
   BibTeX Entry

   @inproceedings{INFER-SVCOMP22, author = {Matthias Kettl and Thomas Lemberger}, title = {The Static Analyzer Infer 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), Part 2}, editor = {Dana Fisman and Grigore Rosu}, pages = {451--456}, year = {2022}, series = {LNCS~13244}, publisher = {Springer}, doi = {10.1007/978-3-030-99527-0_30}, pdf = {https://www.sosy-lab.org/research/pub/2022-SVCOMP.The_Static_Analyzer_Infer_in_SV-COMP.pdf}, presentation = {https://www.sosy-lab.org/research/prs/2022-04-07_TACAS_Infer.pdf}, abstract = {We present Infer-SV, a wrapper that adapts Infer for SV-COMP. Infer is a static-analysis tool for C and other languages, developed by Facebook and used by multiple large companies. It is strongly aimed at industry and the internal use at Facebook. Despite its popularity, there are no reported numbers on its precision and efficiency. With Infer-SV, we take a first step towards an objective comparison of Infer with other SV-COMP participants from academia and industry.}, keyword = {Competition on Software Verification (SV-COMP)}, }

7. 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 Keyword(s): CPAchecker, Software Model Checking, Software Testing Funding: DFG-COOP, DFG-CONVEY, DFG-IDEFIX Publisher's Version PDF Presentation Supplement
   Artifact(s)

   1. doi:10.5281/zenodo.13612338
   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.

8. Matthias Kettl. Adjustable Block Analysis: Actor-Based Creation of Block Summaries for Scaling Formal Verification. Master's Thesis, LMU Munich, Software Systems Lab, 2022. Keyword(s): CPAchecker, Software Model Checking PDF Presentation
   BibTeX Entry

   @misc{Kettl, author = {Matthias Kettl}, title = {Adjustable Block Analysis: Actor-Based Creation of Block Summaries for Scaling Formal Verification}, year = {2022}, pdf = {https://www.sosy-lab.org/research/msc/2022.Kettl.Adjustable_Block_Analysis.pdf}, presentation = {https://www.sosy-lab.org/research/prs/2022-02-24_MA_Adjustable_Block_Analysis.pdf}, keyword = {CPAchecker,Software Model Checking}, howpublished = {Master's Thesis, LMU Munich, Software Systems Lab}, }
9. Matthias Kettl. A Collection of Real-World Benchmark Tasks for Repair of Partial Program Fixes. Research Internship, LMU Munich, Software Systems Lab, 2021.
   BibTeX Entry

   @misc{KettlPartialProgramFixesBenchmarkSet, author = {Matthias Kettl}, title = {A Collection of Real-World Benchmark Tasks for Repair of Partial Program Fixes}, year = {2021}, keyword = {}, howpublished = {Research Internship, LMU Munich, Software Systems Lab}, }
10. Matthias Kettl. Fault Localization for Formal Verification: An Implementation and Evaluation of Algorithms based on Error Invariants and UNSAT-cores. Bachelor's Thesis, LMU Munich, Software Systems Lab, 2020. Keyword(s): CPAchecker, Software Model Checking PDF Presentation
    BibTeX Entry

    @misc{KettlFaultLocalization, author = {Matthias Kettl}, title = {Fault Localization for Formal Verification: An Implementation and Evaluation of Algorithms based on Error Invariants and UNSAT-cores}, year = {2020}, pdf = {https://www.sosy-lab.org/research/bsc/2020.Kettl.Fault_Localization_for_Formal_Verification_An_Implementation_and_Evaluation_of_Algorithms_based_on_Error_Invariants_and_UNSAT-cores.pdf}, presentation = {https://www.sosy-lab.org/research/prs/2020-07-22_BA_FaultLocalizationWithUnsatCores_Kettl.pdf}, keyword = {CPAchecker, Software Model Checking}, annote = {Won the LMU research award for excellent students (LMU Forschungspreis f{\"u}r exzellente Studierende) of LMU Munich}, field = {Computer Science}, howpublished = {Bachelor's Thesis, LMU Munich, Software Systems Lab}, }
    Additional Infos

    Won the LMU research award for excellent students (LMU Forschungspreis für exzellente Studierende) of LMU Munich