Lech Madeyski

2.7k total citations · 1 hit paper
63 papers, 1.5k citations indexed

About

Lech Madeyski is a scholar working on Information Systems, Software and Computer Networks and Communications. According to data from OpenAlex, Lech Madeyski has authored 63 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 53 papers in Information Systems, 40 papers in Software and 6 papers in Computer Networks and Communications. Recurrent topics in Lech Madeyski's work include Software Engineering Research (44 papers), Software Reliability and Analysis Research (32 papers) and Software Engineering Techniques and Practices (26 papers). Lech Madeyski is often cited by papers focused on Software Engineering Research (44 papers), Software Reliability and Analysis Research (32 papers) and Software Engineering Techniques and Practices (26 papers). Lech Madeyski collaborates with scholars based in Poland, United Kingdom and Netherlands. Lech Madeyski's co-authors include Marian Jureczko, Barbara Kitchenham, David Budgen, Pearl Brereton, Richard Torkar, Jacky Keung, Stuart Charters, Shirley Gibbs, Amnart Pohthong and Quang-Vu Nguyen and has published in prestigious journals such as SHILAP Revista de lepidopterología, Statistics in Medicine and IEEE Transactions on Software Engineering.

In The Last Decade

Lech Madeyski

60 papers receiving 1.5k citations

Hit Papers

Towards identifying software project clusters with regard... 2010 2026 2015 2020 2010 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lech Madeyski Poland 19 1.2k 1.1k 296 253 141 63 1.5k
Carmine Gravino Italy 24 1.4k 1.1× 798 0.8× 320 1.1× 458 1.8× 74 0.5× 115 1.6k
Letha H. Etzkorn United States 21 1.5k 1.2× 840 0.8× 370 1.3× 642 2.5× 147 1.0× 94 1.8k
Giuseppe Scanniello Italy 23 1.7k 1.4× 835 0.8× 462 1.6× 626 2.5× 165 1.2× 192 2.1k
Naouel Moha Canada 16 1.1k 0.9× 702 0.7× 448 1.5× 349 1.4× 247 1.8× 57 1.3k
Emelie Engström Sweden 16 941 0.8× 686 0.6× 261 0.9× 352 1.4× 41 0.3× 49 1.3k
Justyna Petke United Kingdom 17 673 0.5× 754 0.7× 179 0.6× 471 1.9× 164 1.2× 70 1.3k
Jens Grabowski Germany 16 734 0.6× 609 0.6× 335 1.1× 239 0.9× 54 0.4× 87 1.1k
Adam Porter United States 25 1.7k 1.4× 1.6k 1.5× 619 2.1× 397 1.6× 113 0.8× 88 2.4k
Miroslaw Staron Sweden 17 836 0.7× 562 0.5× 186 0.6× 280 1.1× 35 0.2× 165 1.2k
Nicholas A. Kraft United States 21 1.4k 1.1× 659 0.6× 319 1.1× 491 1.9× 204 1.4× 72 1.7k

Countries citing papers authored by Lech Madeyski

Since Specialization
Citations

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

Fields of papers citing papers by Lech Madeyski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lech Madeyski

This figure shows the co-authorship network connecting the top 25 collaborators of Lech Madeyski. A scholar is included among the top collaborators of Lech Madeyski 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 Lech Madeyski. Lech Madeyski 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.
Madeyski, Lech, et al.. (2025). Predicting test failures induced by software defects: A lightweight alternative to software defect prediction and its industrial application. Journal of Systems and Software. 223. 112360–112360. 3 indexed citations
2.
Madeyski, Lech, et al.. (2025). “Your AI is impressive, but my code does not have any bugs” managing false positives in industrial contexts. Science of Computer Programming. 246. 103320–103320. 1 indexed citations
3.
Kitchenham, Barbara & Lech Madeyski. (2024). Recommendations for analysing and meta-analysing small sample size software engineering experiments. Empirical Software Engineering. 29(6). 4 indexed citations
4.
Madeyski, Lech, et al.. (2024). Costs and Benefits of Machine Learning Software Defect Prediction: Industrial Case Study. 92–103. 3 indexed citations
5.
Madeyski, Lech, et al.. (2024). Interpretability/Explainability Applied to Machine Learning Software Defect Prediction: An Industrial Perspective. IEEE Software. 42(3). 125–132. 2 indexed citations
6.
Madeyski, Lech, et al.. (2021). OECD Recommendation’s Draft Concerning Access to Research Data from Public Funding: A Review. Bulletin of the Polish Academy of Sciences Technical Sciences. 135401–135401. 2 indexed citations
7.
Madeyski, Lech, et al.. (2021). Cloud Solutions for Private Permissionless Blockchain Deployment. Computing and Informatics. 40(4). 880–896. 1 indexed citations
8.
Madeyski, Lech, et al.. (2020). MLCQ. 342–347. 25 indexed citations
9.
Madeyski, Lech, et al.. (2019). Mutants as Patches: Towards a formal approach to Mutation Testing. Foundations of Computing and Decision Sciences. 44(4). 379–405. 1 indexed citations
10.
Madeyski, Lech. (2017). Software Engineering: Challenges and Solutions : Results of the XVIII KKIO 2016 Software Engineering Conference 2016 held at September 15-17 2016 in Wroclaw, Poland.
11.
Madeyski, Lech & Barbara Kitchenham. (2017). Effect sizes and their variance for AB/BA crossover design studies. Empirical Software Engineering. 23(4). 1982–2017. 25 indexed citations
12.
Madeyski, Lech, et al.. (2016). Factors influencing user story estimations: an industrial interview and a conceptual model. 4(4). 261–280. 5 indexed citations
13.
Madeyski, Lech & Barbara Kitchenham. (2016). Would wider adoption of reproducible research be beneficial for empirical software engineering research?. Journal of Intelligent & Fuzzy Systems. 32(2). 1509–1521. 26 indexed citations
14.
Madeyski, Lech, et al.. (2014). Recent Polish achievements in Software Engineering. 15–38. 1 indexed citations
15.
Jureczko, Marian & Lech Madeyski. (2011). A review of process metrics in defect prediction studies. 133–145. 18 indexed citations
16.
Madeyski, Lech, et al.. (2010). Judy – a mutation testing tool for Java. IET Software. 4(1). 32–42. 56 indexed citations
17.
Madeyski, Lech, et al.. (2007). Impact of aspect-oriented programming on software development efficiency and design quality: an empirical study. IET Software. 1(5). 180–187. 18 indexed citations
18.
Madeyski, Lech. (2006). The Impact of Pair Programming and Test-Driven Development on Package Dependencies in Object-Oriented Design - An Experiment. 1 indexed citations
19.
Madeyski, Lech, et al.. (2005). Architectural design of modern web applications. Foundations of Computing and Decision Sciences. 49–51. 5 indexed citations
20.
Madeyski, Lech, et al.. (2004). E-learning - analiza celów i możliwości ich realizacji na podstawie istniejących specyfikacji i standardów. Prace Naukowe Akademii Ekonomicznej we Wrocławiu. 548–556. 3 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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