Publications

Found 86 results
Author Keyword Title Type [ Year(Desc)]
2018
Antal G, Hegedüs P, Tóth Z, Ferenc R, Gyimóthy T.  2018.  Static JavaScript Call Graphs: A Comparative Study. SCAM. :177-186.
Tóth L, Vidács L.  2018.  Study of Various Classifiers for Identification and Classification of Non-Functional Requirements. Proceedings of the 18th International Conference on Computational Science and Its Applications (ICCSA 2018). 10964:492-503.
Kicsi A, Vidács L, Csuvik V, Horváth F, Beszédes Á, Kocsis F.  2018.  Supporting Product Line Adoption by Combining Syntactic and Textual Feature Extraction. New Opportunities for Software Reuse - 17th International Conference on Software Reuse (ICSR 2018). :1-16.
Hegedüs P.  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.
2019
Csuvik V, Kicsi A, Vidács L.  2019.  Evaluation of Textual Similarity Techniques in Code Level Traceability. Proceedings of the 19th International Conference on Computational Science and Its Applications (ICCSA 2019). :529-543.
Kicsi A, Rákóczi M, Vidács L.  2019.  Exploration and Mining of Source Code Level Traceability Links on Stack Overflow. Proceedings of ICSOFT 2019, 14th International Conference on Software Technologies. :339-346.
Kicsi A, Csuvik V, Vidács L, Horváth F, Beszédes Á, Gyimóthy 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.
Horváth F, Lacerda VSchnepper, Beszédes Á, Vidács L, Gyimóthy 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.
Csuvik V, Kicsi A, Vidács L.  2019.  Source Code Level Word Embeddings in Aiding Semantic Test-to-Code Traceability. Proceedings of the 10th International Workshop on Software and Systems Traceability, (SST 2019 @ ICSE). :29-36.
Tóth L, Vidács L.  2019.  Study of The Performance of Various Classifiers in Labeling Non-Functional Requirements. Information Technology and Control. 48:1-16.
Tóth L, Nagy B, Janthó D, Vidács L, Gyimóthy 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.

Pages