Kmetty Z, Vincze V, Demszky D, Ring O, Nagy B, Szabó MKatalin.  2020.  Pártélet: A Hungarian Corpus of Propaganda Texts from the Hungarian Socialist Era. Proceedings of The 12th Language Resources and Evaluation Conference. :2374-2381.

Kiss Á, Jász J, Lehotai G., Gyimóthy T.  2003.  Interprocedural Static Slicing of Binary Executables. Proceedings of the 3rd IEEE International Workshop on Source Code Analysis and Manipulation (SCAM 2003). :118–127.

Kiss Á, Hodován R, Gyimóthy T.  2018.  HDDr: A Recursive Variant of the Hierarchical Delta Debugging Algorithm. Proceedings of the 9th Workshop on Automating Test Case Design, Selection and Evaluation (A-TEST 2018).

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.

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.

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.

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, Tóth L, Vidács L.  2018.  Exploring the Benefits of Utilizing Conceptual Information in Test-to-Code Traceability. Proceedings of the IEEE/ACM 6th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering (RAISE 2018 @ ICSE).

Kicsi A, Csuvik V, Vidács L, Beszédes Á, Gyimóthy T.  2018.  Feature Level Complexity and Coupling Analysis in 4GL Systems. Proceedings of the 18th International Conference on Computational Science and Its Applications (ICCSA 2018).

Kicsi A, Tóth L, Vidács L.  2018.  Exploring the Benefits of Utilizing Conceptual Information in Test-to-Code Traceability. Proceedings of the IEEE/ACM 6th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering (RAISE 2018 @ ICSE).

Kertész-Farkas A, Fülöp Z, Kocsor A.  2003.  Magyar nyelvû szótárak tömör reprezentációja nemdeterminisztikus automatákkal. I. Magyar Számítógépes Nyelvészet Konferencia. :231-237.

Kalmár Z, Szepesvári C, Lörincz A.  1998.  Module-Based Reinforcement Learning: Experiments with a Real Robot. Machine Learning. 31:55–85.

Kálmán M., Havasi F., Gyimóthy T.  2003.  Compacting XML Documents. SPLST. :137-151.

Kádár I, Hegedüs P, Ferenc R.  2015.  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.

Kádár I, Hegedüs P, Ferenc R.  2014.  Runtime Exception Detection in Java Programs Using Symbolic Execution. Acta Cybernetica. 21:331–352.

Kádár I, Hegedüs P, Ferenc R, Gyimóthy T.  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.

Kádár I, Hegedüs P, Ferenc R, Gyimóthy T.  2016.  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.

Kádár I, Hegedüs P, Ferenc R, Gyimóthy T.  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.