dr hab. inż. Lech Madeyski
Email: lech.madeyski@pwr.edu.pl
Stanowisko: p.o. Kierownika katedry
Jednostka: Wydział Informatyki i Telekomunikacji » Katedra Informatyki Stosowanej
ul. I. Łukasiewicza 3/5, Wrocław
bud. B-4, pok. 4.15
tel. 71 320 2886
Wybrane publikacje |
1 | Artykuł 2024
Interpretability/explainability applied to machine learning software defect prediction: An industrial perspective. IEEE Software. 2024, s. 1-8. ISSN: 0740-7459; 1937-4194 | Zasoby:DOI | |
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2 | 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 | |
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3 | Artykuł 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 | Zasoby:DOISFX | |
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4 | Referat konferencyjny 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 | Zasoby:DOI | |
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5 | Artykuł 2024
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 | |
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6 | Referat konferencyjny 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 | Zasoby:DOI | |
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7 | Referat konferencyjny 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 | Zasoby:DOI | |
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8 | Rozdział w monografii 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 | Zasoby:DOISFX | |
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9 | Artykuł 2023
Continuous build outcome prediction: an experimental evaluation and acceptance modelling. Applied Intelligence. 2023, vol. 53, s. 8673-8692. ISSN: 0924-669X; 1573-7497 | Zasoby:DOISFX | |
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10 | Rozdział w monografii 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 | Zasoby:DOISFX | |
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