Publications

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2024
Horváth F, Aszmann R, Soha PAttila, Beszédes Á, Gyimóthy T.  2024.  Context Switch Sensitive Fault Localization. Proceedings of the 28th International Conference on Evaluation and Assessment in Software Engineering. :110-119.
2023
Csuvik V, Gyimóthy T, Vidács L.  2023.  Can ChatGPT Fix My Code? Proceedings of the 18th International Conference on Software Technologies. :478-485.
Horváth D, Csuvik V, Gyimóthy T, Vidács L.  2023.  An Extensive Study on Model Architecture and Program Representation in the Domain of Learning-based Automated Program Repair. 2023 IEEE/ACM International Workshop on Automated Program Repair (APR). :31-38.
2020
Ferenc R, Gyimesi P, Gyimesi G, Tóth ZGábor, Gyimóthy T.  2020.  An automatically created novel bug dataset and its validation in bug prediction. JOURNAL OF SYSTEMS AND SOFTWARE. 169
Ferenc R, Bán D, Grósz T, Gyimóthy T.  2020.  Deep learning in static, metric-based bug prediction. ARRAY. 6
Kicsi A, Ledenyi KSzabó, Németh P, Pusztai P, Vidács L, Gyimóthy T.  2020.  Elírások automatikus detektálása és javítása radiológiai leletek szövegében. XVI. Magyar Számítógépes Nyelvészeti Konferencia : MSZNY 2020. :191-204.
Horváth F, Beszédes Á, la Vancsics B, Balogh G, Vidács L, Gyimóthy T.  2020.  Experiments with Interactive Fault Localization Using Simulated and Real Users. Proceedings of the 36th IEEE International Conference on Software Maintenance and Evolution (ICSME'20).
Beszédes Á, Horváth F, Di Penta M, Gyimóthy T.  2020.  Leveraging Contextual Information from Function Call Chains to Improve Fault Localization. 2020 IEEE 27th International Conference on Software Analysis, Evolution and Reengineering (SANER). :468-479.
Tóth L, Nagy B, Vidács L, Gyimothy T.  2020.  Mining Hypernyms Semantic Relations from Stack Overflow. Proceedings of the First International Workshop on Knowledge Graph for Software Engineering, KG4SE 2020 - ICSEW. :360-366.
Ferenc R, Tóth ZGábor, Ladányi G, Siket I, Gyimóthy T.  2020.  A public unified bug dataset for java and its assessment regarding metrics and bug prediction. SOFTWARE QUALITY JOURNAL. 28:1447-1506.
Kicsi A, Vidács L, Gyimothy T.  2020.  TestRoutes: A Manually Curated Method Level Dataset for Test-to-Code Traceability. Proceedings of the 17th International Conference on Mining Software Repositories, MSR 2020. :593-597.
Tóth L, Nagy B, Gyimothy T, Vidács L.  2020.  Why Will My Question Be Closed? NLP-Based Pre-Submission Predictions of Question Closing Reasons on Stack Overflow Proceedings of the 42nd International Conference on Software Engineering, NIER Track (ICSE 2020). :105-108.
2019
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.
Horváth F, Gergely Tamás, Beszédes Á, Tengeri D, Balogh G, Gyimothy T.  2019.  Code Coverage Differences of Java Bytecode and Source Code. Software Quality Journal. 27(1):79-123.
Horváth F, Gergely T, Beszédes Á, Tengeri D, Balogh G, Gyimóthy T.  2019.  Code Coverage Differences of Java Bytecode and Source Code Instrumentation Tools. SOFTWARE QUALITY JOURNAL. 27:79-123.
Gergely T, Balogh G, Horváth F, la Vancsics B, Beszédes Á, Gyimóthy T.  2019.  Differences between a static and a dynamic test-to-code traceability recovery method. SOFTWARE QUALITY JOURNAL. 27:797-822.
Kicsi A, Csuvik V, Vidács L, Horváth F, Beszédes Á, Gyimothy T, Kocsis F.  2019.  Feature Analysis using Information Retrieval, Community Detection and Structural Analysis Methods in Product Line Adoption. Journal of Systems and Software. 155:70-90.
Kertész A, Pflanzner T, Gyimóthy T.  2019.  A Mobile IoT Device Simulator for IoT-Fog-Cloud Systems. JOURNAL OF GRID COMPUTING. 17:529-551.
Horváth F, Lacerda VSchnepper, Beszédes Á, Vidács L, Gyimothy T.  2019.  A New Interactive Fault Localization Method with Context Aware User Feedback. Proceedings of the First International Workshop on Intelligent Bug Fixing (IBF 2019). :23-28.
Bán D, Ferenc R, Siket I, Kiss Á, Gyimóthy T.  2019.  Prediction models for performance, power, and energy efficiency of software executed on heterogeneous hardware. JOURNAL OF SUPERCOMPUTING. 75:4001-4025.
Tóth L, Nagy B, Janthó D, Vidács L, Gyimothy T.  2019.  Towards an Accurate Prediction of the Question Quality at Stack Overflow Using a Deep-Learning-Based NLP Approach. Proceedings of ICSOFT 2019, 14th International Conference on Software Technologies. :631-639.