Hegedüs P, Kádár I, Ferenc R, Gyimóthy T.  2018.  Empirical evaluation of software maintainability based on a manually validated refactoring dataset. Information and Software Technology. 95:313-327.

Kádár I, Hegedüs P, Ferenc R, Gyimóthy T.  2016.  Assessment of the Code Refactoring Dataset Regarding the Maintainability of Methods. Computational Science and Its Applications – ICCSA 2016: 16th International Conference, Beijing, China, July 4-7, 2016, Proceedings, Part IV. :610–624.

Kádár I, Hegedüs P, Ferenc R, Gyimóthy T.  2016.  A Code Refactoring Dataset and Its Assessment Regarding Software Maintainability. Proceedings of the 23rd IEEE International Conference on Software Analysis, Evolution, and Reengineering (SANER). 1:599-603.

Kádár I, Hegedüs P, Ferenc R, Gyimóthy T.  2016.  A Manually Validated Code Refactoring Dataset and Its Assessment Regarding Software Maintainability. Proceedings of the 12th International Conference on Predictive Models and Data Analytics in Software Engineering. :10:1–10:4.

Kádár I, Hegedüs P, Ferenc R.  2015.  Adding Constraint Building Mechanisms to a Symbolic Execution Engine Developed for Detecting Runtime Errors. Proceedings of the International Conference on Computational Science and Its Applications – ICCSA 2015. 9159:20-35.

Kádár I, Hegedüs P, Ferenc R.  2014.  Runtime Exception Detection in Java Programs Using Symbolic Execution. Acta Cybernetica. 21:331–352.