Publications
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2024.  Context Switch Sensitive Fault Localization. Proceedings of the 28th International Conference on Evaluation and Assessment in Software Engineering. :110-119.
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2023.  Can ChatGPT Fix My Code? Proceedings of the 18th International Conference on Software Technologies. :478-485.
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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.
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2022.  Premorbid screening of healthy students may carry latent liability for schizophrenia or bipolar affective disorder with neurocognitive and neurophenomenological methods. EUROPEAN PSYCHIATRY. 65:S683-S683.
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2022.  Using contextual knowledge in interactive fault localization. EMPIRICAL SOFTWARE ENGINEERING. 27
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2020.  An automatically created novel bug dataset and its validation in bug prediction. JOURNAL OF SYSTEMS AND SOFTWARE. 169
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2020.  Deep learning in static, metric-based bug prediction. ARRAY. 6
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2020.  Elírások automatikus detektálása és javítása radiológiai leletek szövegében. XVI. Magyar Számítógépes Nyelvészeti Konferencia : MSZNY 2020. :191-204.
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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). 
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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.
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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.
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2020.  A public unified bug dataset for java and its assessment regarding metrics and bug prediction. SOFTWARE QUALITY JOURNAL. 28:1447-1506.
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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.
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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.
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2019.  Challenging Machine Learning Algorithms in Predicting Vulnerable JavaScript Functions. 7th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering. :8-14.
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2019.  Code Coverage Differences of Java Bytecode and Source Code. Software Quality Journal. 27(1):79-123.
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2019.  Code Coverage Differences of Java Bytecode and Source Code Instrumentation Tools. SOFTWARE QUALITY JOURNAL. 27:79-123.
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2019.  Differences between a static and a dynamic test-to-code traceability recovery method. SOFTWARE QUALITY JOURNAL. 27:797-822.
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2019.  Feature Analysis using Information Retrieval, Community Detection and Structural Analysis Methods in Product Line Adoption. Journal of Systems and Software. 155:70-90.
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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.
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2019.  Prediction models for performance, power, and energy efficiency of software executed on heterogeneous hardware. JOURNAL OF SUPERCOMPUTING. 75:4001-4025.
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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.
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2018.  Analysis of Static and Dynamic Test-to-code Traceability Information. Acta Cybernetica. 23:903-919.
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2018.  Differences Between a Static and a Dynamic Test-to-Code Traceability Recovery Method. Software Quality Journal. 27(2):797-822.

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