Szerző: " Csuvik Viktor"

Horváth Dániel; Csuvik Viktor; Gyimóthy Tibor; Vidács László: An Extensive Study on Model Architecture and Program Representation in the Domain of Learning-based Automated Program Repair.
In: 4th International Workshop on Automated Program Repair (APR 2023), 2023.05.16, Melbourne. pp. 31-38.

Lajkó Márk; Horváth Dániel; Csuvik Viktor; Vidács László: Fine-Tuning GPT-2 to Patch Programs, Is It Worth It?
In: Computational Science and Its Applications – ICCSA 2022 Workshops. Lecture Notes in Computer Science, 4 (13380). Springer, Cham, pp. 79-91. (2022) ISBN 978-3-031-10542-5

Lajkó Márk; Csuvik Viktor; Vidács László: Towards JavaScript program repair with Generative Pre-trained Transformer (GPT-2).
In: International Workshop on Automated Program Repair. IEEE Xplore, Pittsburgh (PA), pp. 61-68. (2022) ISBN 9781450392853

Csuvik Viktor; Horváth Dániel; Lajkó Márk; Vidács László: Exploring Plausible Patches Using Source Code Embeddings in JavaScript.
In: 2021 IEEE/ACM International Workshop on Automated Program Repair (APR). Institute of Electrical and Electronics Engineers (IEEE), pp. 11-18. (2021) ISBN 9781665444729

Kicsi András; Csuvik Viktor; Vidács László: Large Scale Evaluation of Natural Language Processing Based Test-to-Code Traceability Approaches.
IEEE ACCESS, 9. pp. 79089-79104. ISSN 2169-3536 (2021)

Csuvik Viktor; Horváth Dániel; Horváth Ferenc; Vidács László: Utilizing Source Code Embeddings to Identify Correct Patches.
In: IBF ’20: Proceedings of the 2020 IEEE 2nd International Workshop on Intelligent Bug Fixing. IEEE, Piscataway (NJ), Amerikai Egyesült Államok, Azonosító: 19455174-Terjedelem: 8 p. (2020) ISBN 9781728162805

Csuvik Viktor; Kicsi András; Vidács László: Evaluation of Textual Similarity Techniques in Code Level Traceability.
LECTURE NOTES IN COMPUTER SCIENCE, 11622. pp. 529-543. ISSN 0302-9743 (2019)

Kicsi András; Csuvik Viktor; Vidács László; Horváth Ferenc; Beszédes Árpád; Gyimóthy Tibor; Kocsis Ferenc: Feature Analysis using Information Retrieval, Community Detection and Structural Analysis Methods in Product Line Adoption.
JOURNAL OF SYSTEMS AND SOFTWARE, 155. pp. 70-90. ISSN 0164-1212 (2019)

Csuvik Viktor; Kicsi András; Vidács László: Source Code Level Word Embeddings in Aiding Semantic Test-to-Code Traceability.
In: 10th International Workshop on Software and Systems Traceability. IEEE, Montreal, pp. 29-36. (2019)

Kicsi András; Csuvik Viktor; Vidács László; Beszédes Árpád; Gyimóthy Tibor: Feature Level Complexity and Coupling Analysis in 4GL Systems.
LECTURE NOTES IN COMPUTER SCIENCE, 10964. pp. 438-453. ISSN 0302-9743 (2018)

Kicsi András; Vidács László; Csuvik Viktor; Horváth Ferenc; Beszédes Árpád; Kocsis Ferenc: Supporting Product Line Adoption by Combining Syntactic and Textual Feature Extraction.
LECTURE NOTES IN COMPUTER SCIENCE, 10826. pp. 148-163. ISSN 0302-9743 (2018)