E-mail: lech.madeyski@pwr.edu.pl

Position: Head of Department

Unit: Faculty of Information and Communication Technology (N) » Department of Applied Informatics

ul. I. Łukasiewicza 3/5, 50-371 Wrocław
building B-4, room 4.15
phone +48 71 320 2886

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Selected publications
1	Article 2024 Szymon Stradowski, Lech Madeyski, Interpretability/explainability applied to machine learning software defect prediction: An industrial perspective. IEEE Software. 2024, s. 1-8. ISSN: 0740-7459; 1937-4194 Resources:DOI
2	Proceeding paper 2024 Krzysztof Wnuk, Lech Madeyski, Waleed Abdeen, Sneha Penmetsa, Navya Lingampalli, An empirical analysis of the usage of requirements attributes in requirements engineering research and practice. W: Computational Collective Intelligence : 16th International Conference, ICCCI 2024 Leipzig, Germany, September 9–11, 2024 : proceedings. Pt. 2 / eds. Ngoc Thanh Nguyen [i in.]. Cham : Springer, cop. 2024. s. 29-40. ISBN: 978-3-031-70818-3; 978-3-031-70819-0 Resources:DOISFX
3	Article 2024 Barbara Kitchenham, Lech Madeyski, Recommendations for analysing and meta-analysing small sample size software engineering experiments. Empirical Software Engineering. 2024, vol. 29, art. nr 137, s. 1-46. ISSN: 1382-3256; 1573-7616 Resources:DOISFX
4	Proceeding paper 2024 Szymon Stradowski, Lech Madeyski, Costs and benefits of machine learning software defect prediction: industrial case study. W: FSE 2024: Companion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering / ed. Marcelo d'Amorim. New York, NY : Association for Computing Machinery, 2024. s. 92-103. ISBN: 979-8-4007-0658-5 Resources:DOI
5	Article 2024 Fahad Al Debeyan, Lech Madeyski, Tracy Hall, David Bowes, The impact of hard and easy negative training data on vulnerability prediction performance. Journal of Systems and Software. 2024, vol. 211, art. 112003, s. 1-13. ISSN: 0164-1212; 1873-1228 Resources:DOISFX
6	Proceeding paper 2023 Szymon Stradowski, Lech Madeyski, Bridging the gap between academia and industry in machine learning software defect prediction: thirteen considerations. W: 38th IEEE/ACM International Conference on Automated Software Engineering, ASE 2023, 11-15 September 2023, Echternach, Luxembourg : proceedings. Piscatway, NJ : IEEE, cop. 2023. s. 1098-1110. ISBN: 979-8-3503-2996-4 Resources:DOI
7	Proceeding paper 2023 Szymon Stradowski, Lech Madeyski, Can we knapsack software defect prediction? Nokia 5G case. W: 2023 IEEE/ACM 45th International Conference on Software Engineering: Companion Proceedings, ICSE-Companion 2023, Melbourne, Australia 15-16 May 2023 : Proceedings. Piscatway, NJ : IEEE, cop. 2023. s. 365-369. ISBN: 979-8-3503-2263-7 Resources:DOI
8	Monograph chapter 2023 Marcel Jerzyk, Lech Madeyski, Code Smells: a comprehensive online catalog and taxonomy. W: Developments in information and knowledge management systems for business applications. Vol. 7 / eds. Natalia Kryvinska, Michal Greguš, Solomiia Fedushko. Cham : Springer, cop. 2023. s. 543-576. ISBN: 978-3-031-25694-3; 978-3-031-25695-0 Resources:DOISFX
9	Article 2023 Marcin Kawalerowicz, Lech Madeyski, Continuous build outcome prediction: an experimental evaluation and acceptance modelling. Applied Intelligence. 2023, vol. 53, s. 8673-8692. ISSN: 0924-669X; 1573-7497 Resources:DOISFX
10	Monograph chapter 2023 Krzysztof Baciejowski, Damian Garbala, Szymon Żmijewski, Lech Madeyski, Are code review smells and metrics useful in pull request-level software defect prediction?. W: Developments in information and knowledge management systems for business applications. Vol. 6 / eds. Natalia Kryvinska, Michal Greguš, Solomiia Fedushko. Cham : Springer, cop. 2023. s. 27-52. ISBN: 978-3-031-27505-0; 978-3-031-27506-7 Resources:DOISFX

All publications