Péter Szécsi

890 total citations
9 papers, 109 citations indexed

About

Péter Szécsi is a scholar working on Software, Computer Networks and Communications and Information Systems. According to data from OpenAlex, Péter Szécsi has authored 9 papers receiving a total of 109 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Software, 2 papers in Computer Networks and Communications and 2 papers in Information Systems. Recurrent topics in Péter Szécsi's work include Software Testing and Debugging Techniques (3 papers), Software System Performance and Reliability (2 papers) and Software Engineering Research (2 papers). Péter Szécsi is often cited by papers focused on Software Testing and Debugging Techniques (3 papers), Software System Performance and Reliability (2 papers) and Software Engineering Research (2 papers). Péter Szécsi collaborates with scholars based in Hungary, United Kingdom and United States. Péter Szécsi's co-authors include Balázs Aczél, Barnabás Szászi, Bence Pálfi, Aba Szollosi, Márton Kovács, Don van den Bergh, Quentin F. Gronau, Márk Zrubka, Eric‐Jan Wagenmakers and Nicholas R. Buttrick and has published in prestigious journals such as Scientific Reports, Cortex and Advances in Methods and Practices in Psychological Science.

In The Last Decade

Péter Szécsi

8 papers receiving 103 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Péter Szécsi Hungary	4	32	21	20	16	13	9	109
Nathan A. Thompson United States	6	7 0.2×	10 0.5×	30 1.5×	14 0.9×	12 0.9×	18	180
Cody D. Christopherson United States	5	19 0.6×	22 1.0×	26 1.3×	34 2.1×	20 1.5×	7	161
Esther Maassen Netherlands	5	12 0.4×	12 0.6×	27 1.4×	24 1.5×	19 1.5×	6	115
Agrima Srivastava India	8	23 0.7×	64 3.0×	14 0.7×	20 1.3×	20 1.5×	17	204
Olav Laudy Netherlands	6	28 0.9×	23 1.1×	33 1.6×	20 1.3×	23 1.8×	13	286
Loukia Tzavella United Kingdom	5	34 1.1×	33 1.6×	22 1.1×	20 1.3×	17 1.3×	8	243
Priya Silverstein United Kingdom	7	27 0.8×	8 0.4×	13 0.7×	16 1.0×	9 0.7×	15	136
Mathijs Mul Netherlands	4	43 1.3×	42 2.0×	9 0.5×	17 1.1×	8 0.6×	6	205
JP Prims United States	3	10 0.3×	34 1.6×	24 1.2×	19 1.2×	4 0.3×	4	115
Carina Prunkl United Kingdom	7	24 0.8×	23 1.1×	10 0.5×	11 0.7×	7 0.5×	11	123

Countries citing papers authored by Péter Szécsi

Since Specialization

Citations

This map shows the geographic impact of Péter Szécsi'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 Péter Szécsi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Péter Szécsi more than expected).

Fields of papers citing papers by Péter Szécsi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Péter Szécsi. 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 Péter Szécsi. The network helps show where Péter Szécsi may publish in the future.

Co-authorship network of co-authors of Péter Szécsi

This figure shows the co-authorship network connecting the top 25 collaborators of Péter Szécsi. A scholar is included among the top collaborators of Péter Szécsi 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 Péter Szécsi. Péter Szécsi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

9 of 9 papers shown

1.

Szécsi, Péter & Barnabás Szászi. (2024). Financial-Scarcity-Related Cues’ Impact on the Cognitive Performance of the Poor: A Meta-analysis. Collabra Psychology. 10(1).

2.

Szászi, Barnabás, Bence Pálfi, Péter Szécsi, et al.. (2023). Does alleviating poverty increase cognitive performance? Short- and long-term evidence from a randomized controlled trial. Cortex. 169. 81–94. 2 indexed citations

3.

Szászi, Barnabás, Nándor Hajdú, Péter Szécsi, Elizabeth Tipton, & Balázs Aczél. (2022). A machine learning analysis of the relationship of demographics and social gathering attendance from 41 countries during pandemic. Scientific Reports. 12(1). 724–724. 3 indexed citations

4.

Szécsi, Péter, et al.. (2020). Report on the Differential Testing of Static Analyzers. Acta Cybernetica. 25(4). 781–795. 4 indexed citations

5.

Szécsi, Péter, et al.. (2020). Improved Loop Execution Modeling in the Clang Static Analyzer. Acta Cybernetica. 25(4). 909–921. 3 indexed citations

6.

Buttrick, Nicholas R., Balázs Aczél, Lena Fanya Aeschbach, et al.. (2020). Many Labs 5: Registered Replication of Vohs and Schooler (2008), Experiment 1. Advances in Methods and Practices in Psychological Science. 3(3). 429–438. 11 indexed citations

7.

Aczél, Balázs, Bence Pálfi, Aba Szollosi, et al.. (2018). Quantifying Support for the Null Hypothesis in Psychology: An Empirical Investigation. Advances in Methods and Practices in Psychological Science. 1(3). 357–366. 78 indexed citations

8.

Szécsi, Péter, et al.. (2018). [Engineering Paper] Challenges of Implementing Cross Translation Unit Analysis in Clang Static Analyzer. 171–176. 7 indexed citations

9.

Horväth, Gábor, et al.. (2018). Implementation and evaluation of cross translation unit symbolic execution for C family languages. 428–428. 1 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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