TU Wien Informatics

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Maria Christakis

Univ.Prof.in Dr.in sc.

Maria Christakis

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

  • 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

Contact

2023W

2024S

 

  • Automatically Testing Functional Properties of Code Translation Models / 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)
  • 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
  • Dependency-Aware Metamorphic Testing of Datalog Engines / Numair Mansur, M., Wüstholz, V., & Christaki, 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)
  • Green Fuzzer Benchmarking / Ounjai, J., Wüstholz, V., & Christaki, 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)
  • 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
  • Synthesizing a Progression of Subtasks for Block-Based Visual Programming Tasks / 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)
  • Automatic Metamorphic Test Oracles for Action-Policy Testing / Eisenhut, J., Torralba, Á., Christaki, 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 / 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 (2022–2025)
  • 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
  • Rigorous Methods for Smart Contracts / 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)