Publications

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2015
Szőke G, Nagy C, Fülöp L J, Ferenc R, Gyimóthy T.  2015.  FaultBuster: An Automatic Code Smell Refactoring Toolset. Proceedings of the 15th International Working Conference on Source Code Analysis and Manipulation (SCAM 2015). :253–258.
Faragó C, Hegedűs P, Ladányi G, Ferenc R.  2015.  Impact of Version History Metrics on Maintainability. Proceedings of the 8th International Conference on Advanced Software Engineering & Its Applications (ASEA 2015). :30–35.
Ujhelyi Z, Szőke G, Horváth Á, Csiszár NIstván, Vidács L, Varró D, Ferenc R.  2015.  Performance Comparison of Query-based Techniques for Anti-pattern Detection. Information and Software Technology. 65:147–165.
Bán D, Ferenc R, Siket István, Kiss Á.  2015.  Prediction Models for Performance, Power, and Energy Efficiency of Software Executed on Heterogeneous Hardware. Proceedings of the 13th IEEE International Symposium on Parallel and Distributed Processing with Applications (ISPA 2015). :178–183.
Ladányi G, Tóth Z, Ferenc R, Keresztesi T.  2015.  A Software Quality Model for RPG. Proceedings of the 22nd IEEE International Conference on Software Analysis, Evolution, and Reengineering (SANER 2015). :91–100.
2016
[Anonymous].  2016.  10th Jubilee Conference of PhD Students in Computer Science (CSCS 2016).
Kádár I, Hegedűs P, Ferenc R, Gyimóthy T.  2016.  Assessment of the Code Refactoring Dataset Regarding the Maintainability of Methods. Proceedings of the 16th International Conference on Computational Science and Its Applications (ICCSA 2016). :610–624.
Kádár I, Hegedűs 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 2016). :599–603.
Szőke G, Nagy C, Ferenc R, Gyimóthy T.  2016.  Designing and Developing Automated Refactoring Transformations: An Experience Report. Proceedings of the 23rd IEEE International Conference on Software Analysis, Evolution, and Reengineering (SANER 2016). :693–697.
Gyimesi G, Bán D, Siket István, Ferenc R, Brugnoni S, Corbat T, Sommerlad P, Suter T.  2016.  Enforcing Techniques and Transformation of C/C++ Source Code to Heterogeneous Hardware. Proceedings of the 16th IEEE International Conference on Scalable Computing and Communication (ScalCom 2016). :1173–1180.
Kádár I, Hegedűs P, Ferenc R, Gyimóthy T.  2016.  A Manually Validated Code Refactoring Dataset and Its Assessment Regarding Software Maintainability. Proceedings of the 12th ACM International Conference on Predictive Models and Data Analytics in Software Engineering (PROMISE 2016). :10:1–10:4.
Tóth Z, Gyimesi P, Ferenc R.  2016.  A Public Bug Database of GitHub Projects and Its Application in Bug Prediction. Proceedings of the 16th International Conference on Computational Science and Its Applications (ICCSA 2016). :625–638.
Antal G, Havas D, Siket István, Beszédes Á, Ferenc R, Mihalicza J.  2016.  Transforming C++11 Code to C++03 to Support Legacy Compilation Environments. Proceedings of 16th IEEE International Working Conference on Source Code Analysis and Manipulation (SCAM'16). :177-186.
2017
Szőke G, Antal G, Nagy C, Ferenc R, Gyimóthy T.  2017.  Empirical Study on Refactoring Large-scale Industrial Systems and Its Effects on Maintainability. Journal of Systems and Software. 129:107–126.
2018
Hegedűs 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
Bán D, Ferenc R, Siket I, Kiss Á, Gyimóthy T.  2018.  Prediction Models for Performance, Power, and Energy Efficiency of Software Executed on Heterogeneous Hardware. Journal of Supercomputing. :25.
2019
Gyimesi P, Vancsics B, Stocco A, Mazinanian D, Beszédes Á, Ferenc R, Mesbah A.  2019.  BugsJS: a Benchmark of JavaScript Bugs. 2019 12th IEEE Conference on Software Testing, Validation and Verification (ICST). :90-101.
Ferenc R, Hegedűs P, Gyimesi P, Antal G, Bán D, Gyimothy T.  2019.  Challenging Machine Learning Algorithms in Predicting Vulnerable JavaScript Functions. 7th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering. :8-14.