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	Referat konferencyjny 2025 Fahad Al Debeyan, Tracy Hall, Lech Madeyski, Emerging results in using explainable AI to improve software vulnerability prediction. W: FSE Companion ’25 : Companion Proceedings of the 33rd ACM International Conference on the Foundations of Software Engineering / ed. Jingyue Li. New York, NY : Association for Computing Machinery, cop. 2025. s. 561-565. ISBN: 979-8-4007-1276-0 Zasoby:DOIURL
2	Artykuł 2025 Szymon Stradowski, Lech Madeyski, “Your AI is impressive, but my code does not have any bugs” managing false positives in industrial contexts. Science of Computer Programming. 2025, vol. 246, art. 103320, s. 1-5. ISSN: 0167-6423; 1872-7964 Zasoby:DOIURLSFX
3	Artykuł 2025 Lech Madeyski, Szymon Stradowski, Predicting test failures induced by software defects: a lightweight alternative to software defect prediction and its industrial application. Journal of Systems and Software. 2025, vol. 223, art. 112360, s. 1-18. ISSN: 0164-1212; 1873-1228 Zasoby:DOIURLSFX
4	Artykuł 2025 Szymon Stradowski, Lech Madeyski, Interpretability/explainability applied to machine learning software defect prediction: An industrial perspective. IEEE Software. 2025, vol. 42, nr 3, s. 125-132. ISSN: 0740-7459; 1937-4194 Zasoby:DOISFX
5	Referat konferencyjny 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 Zasoby:DOISFX
6	Artykuł 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 Zasoby:DOISFX
7	Referat konferencyjny 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 Zasoby:DOI
8	Artykuł 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 Zasoby:DOISFX
9	Referat konferencyjny 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 Zasoby:DOI
10	Referat konferencyjny 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 Zasoby:DOI

All publications