Maria Christakis
Univ.Prof.in Dr.in sc.
About
Maria Christakis's research goal is to develop theoretical foundations and practical tools for building more reliable and usable software and increasing developer productivity. She is primarily interested in software engineering and formal methods. Maria particularly likes investigating topics in automatic test generation, program analysis, and software verification. Her tools and techniques explore novel ways in writing, specifying, verifying, testing, and debugging programs in order to make them more robust while improving the developer experience.
For more information, please visit her personal website.
Roles
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Head of Research Unit
Software Engineering, E194-01 -
Full Professor
Software Engineering, E194-01 -
Curriculum Coordinator
Bachelor Informatics / Specialization Software Engineering -
Curriculum Coordinator
Master Software Engineering and Internet Computing -
Faculty Council
Principal Member
Courses
2024W
- Advanced Software Engineering / 194.021 / VU
- Bachelor Thesis / 188.919 / PR
- Project in Computer Science 1 / 194.145 / PR
- Seminar for Master Students in Software Engineering & Internet Computing / 180.777 / SE
- Seminar in Software Engineering / 194.127 / SE
- Software Engineering / 194.020 / VU
2025S
- Project in Computer Science 1 / 194.145 / PR
- Project in Computer Science 2 / 194.146 / PR
Projects
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Types4Strings: Types for Strings
2024 – 2027 / Austrian Science Fund (FWF) -
Amazon Research Award for conducting research on "Testing Dafny for Unsoundness and Brittleness Bugs"
2024 – 2027 / Amazon Research Awards -
Testing Program Analyzers Ad Absurdum
2023 – 2028 / European Commission
Publications: 188016 / 188021 / 204056 -
Effective Formal Methods for Smart-Contract Certification
2023 – 2027 / Vienna Science and Technology Fund (WWTF)
Publications: 192933 / 199514 / 199522 / 203882 / 203672 / 202379 / 203892 / 204116 -
Cloud Open Source Research Mobility Network
2023 – 2026 / European Commission -
Facebook Faculty Research Award for significant research contributions in the area
of Program Analysis
2022 – 2030 / Max-Planck-Gesellschaft zur Förderu der Wissenschaften e.V. -
Google Research Scholar Award for conducting research on "Metamorphic Specification and Testing of Machine-Learning Models"
2022 – 2030 / Max-Planck-Gesellschaft zur Förderu der Wissenschaften e.V.
Publication: 188066 -
EFFECTIVE CONSTRUCTION OF PROBABILISTIC HYBRID SEMI-PARAMETRIC MODELS FOR MODEL-BASED CONDITION MONITORING AND ACCELERATED MATERIAL DESIGN
2022 – 2027 / Austrian Research Promotion Agency (FFG) -
Software Assistants for Probabilistic Programming
2022 – 2026 / Meta Platforms, Inc. -
Future Teachers Education: Computational Thinking and STEAM
2019 – 2022 / European Commission
Publication: 153710 -
Bebras: international Challenge on Informatics and Computational Thinking
2007 – 2027 / Biber der Informatik
Publication: 189823
Publications
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Inductive Predicate Synthesis Modulo Programs (Extended)
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Wesley, S., Christakis, M., Navas, J. A., Trefler, R., Wüstholz, V., & Gurfinkel, A. (2024). Inductive Predicate Synthesis Modulo Programs (Extended). arXiv. https://doi.org/10.34726/7020
Download: Preprint (1.24 MB)
Project: ForSmart (2023–2027) -
Automatically Testing Functional Properties of Code Translation Models
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Eniser, H. F., Wüstholz, V., & Christakis, M. (2024). Automatically Testing Functional Properties of Code Translation Models. In Proceedings of the 38th AAAI Conference on Artificial Intelligence (pp. 21055–21062). AAAI Press. https://doi.org/10.1609/aaai.v38i19.30097
Download: PDF (155 KB) -
Towards Translating Real-World Code with LLMs: A Study of Translating to Rust
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Eniser, H. F., Zhang, H., David, C., Wang, M., Christakis, M., Paulsen, B., Dodds, J., & Kroening, D. (2024). Towards Translating Real-World Code with LLMs: A Study of Translating to Rust. arXiv. https://doi.org/10.48550/arXiv.2405.11514
Download: The technical report (466 KB) -
Constraint-Based Test Oracles for Program Analyzers
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Fleischmann, M., Kaindlstorfer, D. M., Isychev, A., Wüstholz, V., & Christakis, M. (2024). Constraint-Based Test Oracles for Program Analyzers. In F. Vladimir, B. Ray, & M. Zhou (Eds.), ASE ’24: Proceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering (pp. 344–355). Association for Computing Machinery. https://doi.org/10.1145/3691620.3695035
Download: PDF (712 KB)
Project: MirandaTesting (2023–2028) -
Inductive Predicate Synthesis Modulo Programs
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Wesley, S., Christakis, M., Navas, J. A., Trefler, R., Wüstholz, V., & Gurfinkel, A. (2024). Inductive Predicate Synthesis Modulo Programs. In 38th European Conference on Object-Oriented Programming (ECOOP 2024) (pp. 1–30). https://doi.org/10.4230/LIPIcs.ECOOP.2024.43
Download: PDF (1.18 MB)
Project: ForSmart (2023–2027) - ISSTA 2024: Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis / Christakis, M., & Pradel, M. (Eds.). (2024). ISSTA 2024: Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis. https://doi.org/10.1145/3650212
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Verifying Global Two-Safety Properties in Neural Networks with Confidence
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Athavale, A., Bartocci, E., Christakis, M., Maffei, M., Ničković, D., & Weissenbacher, G. (2024). Verifying Global Two-Safety Properties in Neural Networks with Confidence. In A. Gurfinkel & V. Ganesh (Eds.), Computer Aided Verification (pp. 329–351). Springer. https://doi.org/10.1007/978-3-031-65630-9_17
Projects: Browsec (2018–2024) / ForSmart (2023–2027) / ProbInG (2020–2025) / SFB SPyCoDe (2023–2026) / TAIGER (2023–2027) - New fuzzing biases for action policy testing / Eisenhut, J., Schuler, X., Fiser, D., Höller, D., Christakis, M., & Hoffmann, J. (2024). New fuzzing biases for action policy testing. In Vol. 34 (2024): Proceedings of the Thirty-Fourth International Conference on Automated Planning and Scheduling. 34th International Conference on Automated Planning and Scheduling (ICAPS 2024), Banaff, Alberta, Canada. AAAI Press.
- Specifying and Testing k-Safety Properties for Machine-Learning Models / Christakis, M. (2023, November 8). Specifying and Testing k-Safety Properties for Machine-Learning Models [Presentation]. 68th IFIP WG2.4 (Online) Meeting on Software Implementation Technology, Austria.
- Automatically Testing Functional Properties of Code Translation Models / Eniser, H. F., Wüstholz, V., & Christaki, M. (2023). Automatically Testing Functional Properties of Code Translation Models. https://doi.org/10.48550/arXiv.2309.12813
- Rigorous Software Engineering / Christaki, M. (2023, July 26). Rigorous Software Engineering [Presentation]. Microsoft Research talks, Redmond, United States of America (the). http://hdl.handle.net/20.500.12708/187864
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Green Fuzzer Benchmarking
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Ounjai, J., Wüstholz, V., & Christakis, M. (2023). Green Fuzzer Benchmarking. In ISSTA 2023: Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis (pp. 1396–1406). Association for Computing Machinery. https://doi.org/10.1145/3597926.3598144
Download: PDF (307 KB)
Project: MirandaTesting (2023–2028) -
Dependency-Aware Metamorphic Testing of Datalog Engines
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Numair Mansur, M., Wüstholz, V., & Christakis, M. (2023). Dependency-Aware Metamorphic Testing of Datalog Engines. In ISSTA 2023: Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis (pp. 236–247). Association for Computing Machinery. https://doi.org/10.1145/3597926.3598052
Download: PDF (398 KB)
Project: MirandaTesting (2023–2028) - Rigorous Software Engineering / Christaki, M. (2023, June 13). Rigorous Software Engineering [Keynote Presentation]. SBA IMPACT 2023, Wien, Austria. http://hdl.handle.net/20.500.12708/187788
- Rigorous Software Engineering / Christaki, M. (2023, February 2). Rigorous Software Engineering [Presentation]. Automated Reasoning Symposium Technical Talk, United States of America (the). http://hdl.handle.net/20.500.12708/187849
- Software Bug Detection: Challenges and Synergies / Böhme, M., Christaki, M., Padhye, R., Serebryany, K., Zeller, A., & Eniser, H. F. (2023). Software Bug Detection: Challenges and Synergies. https://doi.org/https://doi.org/10.4230/DagRep.13.3.92
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Automatic Metamorphic Test Oracles for Action-Policy Testing
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Eisenhut, J., Torralba, Á., Christakis, M., & Hoffmann, J. (2023). Automatic Metamorphic Test Oracles for Action-Policy Testing. In S. Koenig, R. Stern, & M. Vallati (Eds.), Proceedings of the Thirty-Third International Conference on Automated Planning and Scheduling (pp. 109–117). Association for the Advancement of Artificial Intelligence. https://doi.org/10.1609/icaps.v33i1.27185
Download: PDF (313 KB) -
Specifying and Testing k-Safety Properties for Machine-Learning Models
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Christaki, M., Eniser, H. F., Hoffmann, J., Singla, A., & Wüstholz, V. (2023). Specifying and Testing k-Safety Properties for Machine-Learning Models. In Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI-23) (pp. 4748–4757). International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2023/528
Download: PDF (327 KB)
Project: Nomos (2022–2030) -
Synthesizing a Progression of Subtasks for Block-Based Visual Programming Tasks
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Tercan, A., Ghosh, A., Eniser, H. F., Christaki, M., & Singla, A. (2023). Synthesizing a Progression of Subtasks for Block-Based Visual Programming Tasks. https://doi.org/10.48550/arXiv.2305.17518
Download: PDF (2.37 MB) -
Rigorous Methods for Smart Contracts
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Bjørner, N., Christakis, M., Maffei, M., & Rosu, G. (Eds.). (2022). Rigorous Methods for Smart Contracts (Dagstuhl Seminar 21431). Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH, Dagstuhl Publishing. https://doi.org/10.4230/DagRep.11.9.80
Projects: Browsec (2018–2024) / Ethertrust (2018–2019) / PR4DLT (2018–2021) / PROFET (2019–2023)
Supervisions
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Metamorphic Testing of ZKC Infrastructure
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Leeb, P. (2024). Metamorphic Testing of ZKC Infrastructure [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2024.116110
Download: PDF (528 KB) - Automated soundness testing of program analyzers / Fleischmann, M. (2024). Automated soundness testing of program analyzers [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2024.109940
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Generating multi-lingual, semantically equivalent fuzzer benchmarks from mazes
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Chadt, J. (2024). Generating multi-lingual, semantically equivalent fuzzer benchmarks from mazes [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2024.115005
Download: PDF (552 KB)