Lech Madeyski, DSc, PhD, Eng
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
Selected publications |
1 | Article 2025
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 | Resources:DOIURLSFX |     |
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2 | Article 2024
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 |    |
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3 | Proceeding paper 2024
Krzysztof Wnuk, 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 | |
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4 | Article 2024
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 |     |
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5 | Proceeding paper 2024
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 |  |
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6 | Article 2024
Fahad Al Debeyan, 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 |     |
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7 | Proceeding paper 2023
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 | |
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8 | Proceeding paper 2023
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 | |
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9 | Monograph chapter 2023
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 | |
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10 | Article 2023
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 |    |
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All publications