Machine Learning and Static Analysis for Building Software Verification Portfolios

Are you interested in Machine Learning and Formal Methods?

We are looking for students to work on Verifolio, our machine learning-based portfolio software verifier.
Verifolio uses static analysis and machine learning to automatically pick a suitable verification tool for a given verification task.

Currently, Verifolio is trained and evaluated on data from the Intl. Competition on Software Verification (SV-COMP) using Support Vector Machines (SVM). It outperforms any standalone software verifier in the competition. We are looking for motivated students who will

  • update Verifolio to the latest edition of SV-COMP (SV-COMP’17)
  • facilitate further machine learning algorithms, in particular (deep) neural networks
  • advance our understanding of the trained model (e.g., for feature selection)
  • implement new static analyses to extend our feature set
  • improve our infrastructure for running experiments

 

[Contact Florian ZulegerThomas Pani]

Latest News

Profil article on women in logic

A recent article in the Austrian weekly Profil about female logicians in Austria is featuring Agata Ciabattoni, Martina Seidl, Laura Kovacs, Magdalena Ortiz, Marijana Lazic, Shqiponja Ahmetaj, and Neha Lodha. All women are affiliated with the Doctoral College Logical Methods in Computer Science.  

Continue reading

WWTF ICT project awarded to Igor Konnov

Igor Konnov (PI), together with Josef Widder (co-PI) and Helmut Veith (core team), are awarded an ICT research project APALACHE “Abstraction-based Parameterized TLA Checker” by the Vienna Science and Technology Fund WWTF.

Continue reading

Full news archive