Publications
Found 24 results
Author Keyword Title Type [ Year] Filters: Author is Hegedűs, Péter [Clear All Filters]
Deep-water framework: The Swiss army knife of humans working with machine learning models. SoftwareX. 12:100551.
.
2020. Exploring the Security Awareness of the Python and JavaScript Open Source Communities. Proceedings of the 17th International Conference on Mining Software Repositories (MSR). :16–20.
.
2020. Challenging Machine Learning Algorithms in Predicting Vulnerable JavaScript Functions. Proceedings of the 7th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering. :8–14.
.
2019. .
2019. Developer Focus: Lack of Impact on Maintainability. Proceedings of the International Conference on Computational Science and Its Applications – ICCSA 2018. 10964:391–402.
.
2018. Empirical evaluation of software maintainability based on a manually validated refactoring dataset. Information and Software Technology. 95:313-327.
.
2018. A Hands-on OpenStack Code Refactoring Experience Report. Proceedings of the International Conference on Computational Science and Its Applications – ICCSA 2018. 10964:464–480.
.
2018. Static JavaScript Call Graphs: A Comparative Study. SCAM. :177-186.
.
2018. Towards Analyzing the Complexity Landscape of Solidity Based Ethereum Smart Contracts. Proceedings of the 1st International Workshop on Emerging Trends in Software Engineering for Blockchain. :35–39.
.
2018. 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.
.
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.
.
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.
.
2016. 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.
.
2015. Advances in Software Product Quality Measurement and Its Applications in Software Evolution. Proceedings of the International Conference on Software Maintenance and Evolution. :590–593.
.
2015. Code Ownership: Impact on Maintainability. Proceedings of the International Conference on Computational Science and Its Applications – ICCSA 2015. 9159:3-19.
.
2015. Cumulative Code Churn: Impact on Maintainability. Proceedings of the 15th IEEE International Working Conference on Source Code Analysis and Manipulation (SCAM). :141-150.
.
2015. Do Automatic Refactorings Improve Maintainability? An Industrial Case Study Proceedings of the 31st International Conference on Software Maintenance and Evolution – ICSME'15. :429–438.
.
2015. Impact of Version History Metrics on Maintainability. Proceedings of the 2015 International Conference on Advanced Software Engineering & Its Applications. :30–35.
.
2015. Connection Between Version Control Operations and Quality Change of the Source Code. {Acta Cybernetica}. 21:585–607.
.
2014. The Connection of the Bug Density and Maintainability of Classes. 8th International Workshop on Software Quality and Maintainability.
.
2014. The Impact of Version Control Operations on the Quality Change of the Source Code. Proceedings of the International Conference on Computational Science and Its Applications–ICCSA 2014. :353–369.
.
2014. QualityGate SourceAudit: a Tool for Assessing the Technical Quality of Software. Proceedings of the CSMR-WCRE 2014 Software Evolution Week (Merger of the 18th IEEE European Conference on Software Maintenance and Reengineering & 21st IEEE Working Conference on Reverse Engineering - CSMR-WCRE 2014). :440–445.
.
2014. Runtime Exception Detection in Java Programs Using Symbolic Execution. Acta Cybernetica. 21:331–352.
.
2014. Software Product Quality Models. {Evolving Software Systems}. :65-100.
.
2014.