László Vidács

658 total citations
48 papers, 372 citations indexed

About

László Vidács is a scholar working on Information Systems, Software and Artificial Intelligence. According to data from OpenAlex, László Vidács has authored 48 papers receiving a total of 372 indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Information Systems, 25 papers in Software and 19 papers in Artificial Intelligence. Recurrent topics in László Vidács's work include Software Engineering Research (32 papers), Software Testing and Debugging Techniques (24 papers) and Software Reliability and Analysis Research (20 papers). László Vidács is often cited by papers focused on Software Engineering Research (32 papers), Software Testing and Debugging Techniques (24 papers) and Software Reliability and Analysis Research (20 papers). László Vidács collaborates with scholars based in Hungary, Australia and Netherlands. László Vidács's co-authors include Árpád Beszédes, Tibor Gyimóthy, Rudolf Ferenć, László Tóth, Ferenc Horváth, Lóránt Farkas, Martin Pinzger, Tamás Gergely, Csaba Nagy and Zoltán Ujhelyi and has published in prestigious journals such as IEEE Access, IEEE Transactions on Software Engineering and Journal of Systems and Software.

In The Last Decade

László Vidács

45 papers receiving 346 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
László Vidács Hungary 12 259 211 114 94 59 48 372
Zhiyi Ma China 10 289 1.1× 216 1.0× 120 1.1× 107 1.1× 37 0.6× 45 370
A. Svyatkovskiy United States 6 360 1.4× 196 0.9× 211 1.9× 90 1.0× 110 1.9× 8 475
Shangqing Liu Singapore 10 276 1.1× 149 0.7× 124 1.1× 78 0.8× 124 2.1× 23 381
Van Nguyen Australia 10 239 0.9× 159 0.8× 106 0.9× 75 0.8× 115 1.9× 27 358
Ian Bayley United Kingdom 11 232 0.9× 132 0.6× 254 2.2× 101 1.1× 30 0.5× 44 396
Antonio Mastropaolo Switzerland 9 267 1.0× 163 0.8× 150 1.3× 94 1.0× 37 0.6× 28 381
Mário Jino Brazil 11 304 1.2× 261 1.2× 85 0.7× 159 1.7× 84 1.4× 68 471
Manar H. Alalfi Canada 12 337 1.3× 224 1.1× 139 1.2× 100 1.1× 103 1.7× 46 401
Simon Poulding United Kingdom 11 222 0.9× 239 1.1× 88 0.8× 47 0.5× 26 0.4× 34 340
Josip Božić Austria 12 160 0.6× 127 0.6× 121 1.1× 58 0.6× 97 1.6× 23 303

Countries citing papers authored by László Vidács

Since Specialization
Citations

This map shows the geographic impact of László Vidács's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by László Vidács with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites László Vidács more than expected).

Fields of papers citing papers by László Vidács

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by László Vidács. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by László Vidács. The network helps show where László Vidács may publish in the future.

Co-authorship network of co-authors of László Vidács

This figure shows the co-authorship network connecting the top 25 collaborators of László Vidács. A scholar is included among the top collaborators of László Vidács based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with László Vidács. László Vidács is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Teusink, Bas, et al.. (2025). MINN: A metabolic-informed neural network for integrating omics data into genome-scale metabolic modeling. Computational and Structural Biotechnology Journal. 27. 3609–3617. 1 indexed citations
2.
Vidács, László, et al.. (2025). Introducing MLOps to Facilitate the Development of Machine Learning Models in Agronomy: A Case Study. IEEE Access. 13. 122059–122070.
3.
Vidács, László, et al.. (2024). Radiologic text correction for better machine understanding. Engineering Reports. 6(12).
4.
Vidács, László, et al.. (2024). GenProgJS: A Baseline System for Test-Based Automated Repair of JavaScript Programs. IEEE Transactions on Software Engineering. 51(2). 325–343. 1 indexed citations
5.
Gyimóthy, Tibor, et al.. (2024). Automated Program Repair with the GPT Family, including GPT-2, GPT-3 and CodeX. 34–41. 2 indexed citations
6.
Vidács, László, et al.. (2024). Yet Another Miner Utility Unveiling a Dataset: CodeGrain. 338–345. 1 indexed citations
7.
Gyimóthy, Tibor, et al.. (2023). Can ChatGPT Fix My Code?. 478–485. 1 indexed citations
8.
Horváth, Ferenc, et al.. (2022). Using contextual knowledge in interactive fault localization. Empirical Software Engineering. 27(6). 3 indexed citations
9.
Vidács, László, et al.. (2022). Towards JavaScript program repair with generative pre-trained transformer (GPT-2). SZTE Publicatio Repozitórium (University of Szeged). 61–68. 26 indexed citations
10.
Pusztai, Péter, et al.. (2021). Automatic Classification and Entity Relation Detection in Hungarian Spinal MRI Reports. SZTE Publicatio Repozitórium (University of Szeged). 13–19. 2 indexed citations
11.
Vidács, László, et al.. (2020). TestRoutes. SZTE Publicatio Repozitórium (University of Szeged). 593–597. 4 indexed citations
12.
Horváth, Ferenc, et al.. (2019). A New Interactive Fault Localization Method with Context Aware User Feedback. SZTE Publicatio Repozitórium (University of Szeged). 32. 23–28. 5 indexed citations
13.
14.
Vidács, László, et al.. (2017). Information retrieval based feature analysis for product line adoption in 4GL systems. SZTE Publicatio Repozitórium (University of Szeged). 6786. 1–6. 2 indexed citations
15.
Ujhelyi, Zoltán, et al.. (2015). Performance comparison of query-based techniques for anti-pattern detection. Information and Software Technology. 65. 147–165. 13 indexed citations
16.
Horváth, Ferenc, et al.. (2015). Test suite evaluation using code coverage based metrics. 46–60. 10 indexed citations
17.
Nagy, Csaba, et al.. (2010). MAGISTER: Quality assurance of Magic applications for software developers and end users. 1. 1–6. 6 indexed citations
18.
Vidács, László, Árpád Beszédes, & Tibor Gyimóthy. (2009). Combining preprocessor slicing with C/C++ language slicing. Science of Computer Programming. 74(7). 399–413. 5 indexed citations
19.
Vidács, László, et al.. (2008). Combining Preprocessor Slicing with C/C++ Language Slicing. SZTE Publicatio Repozitórium (University of Szeged). 163–171. 3 indexed citations
20.
Vidács, László, Árpád Beszédes, & Rudolf Ferenć. (2004). Columbus schema for C/C++ preprocessing. SZTE Publicatio Repozitórium (University of Szeged). 75–84. 23 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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