Search Results - "Madeyski, Lech"

Empirical evaluation of continuous test-driven development in industrial settings.

Authors: Madeyski, Lech Kawalerowicz, Marcin Nguyen, Ngoc Thanh et al.

Source: Journal of Intelligent & Fuzzy Systems; 2019, Vol. 37 Issue 6, p7643-7655, 13p

Technical Debt Aware Estimations in Software Engineering: A Systematic Mapping Study.

Authors: Klimczyk, Paweł Madeyski, Lech

Source: e-Informatica; 2020, Vol. 14 Issue 1, p61-76, 16p

Recommendations for analysing and meta-analysing small sample size software engineering experiments.

Authors: Kitchenham, Barbara Madeyski, Lech

Source: Empirical Software Engineering; Nov2024, Vol. 29 Issue 6, p1-46, 46p

Can We Knapsack Software Defect Prediction? Nokia 5G Case.

Authors: Stradowski, Szymon Madeyski, Lech

Source: ICSE: International Conference on Software Engineering; 2023, p365-369, 5p

How vulnerability explanations help software practitioners confirm and fix code vulnerabilities.

Authors: Al Debeyan, Fahad Hall, Tracy Madeyski, Lech et al.

Source: Information & Software Technology; Jul2026, Vol. 195, pN.PAG-N.PAG, 1p

Test case prioritization: A systematic review using snowballing and TCPFramework with approach combinators.

Authors: Chojnacki, Tomasz Madeyski, Lech

Source: Information & Software Technology; Jun2026, Vol. 194, pN.PAG-N.PAG, 1p

Continuous build outcome prediction: an experimental evaluation and acceptance modelling.

Authors: Kawalerowicz, Marcin Madeyski, Lech

Source: Applied Intelligence; Apr2023, Vol. 53 Issue 8, p8673-8692, 20p

"Your AI is impressive, but my code does not have any bugs" managing false positives in industrial contexts.

Authors: Stradowski, Szymon Madeyski, Lech

Source: Science of Computer Programming; Dec2025, Vol. 246, pN.PAG-N.PAG, 1p

Which process metrics can significantly improve defect prediction models? An empirical study.

Authors: Madeyski, Lech Jureczko, Marian

Source: Software Quality Journal; Sep2015, Vol. 23 Issue 3, p393-422, 30p

OECD Recommendation's draft concerning access to research data from public funding: A review.

Authors: MADEYSKI, Lech LEWOWSKI, Tomasz KITCHENHAM, Barbara

Source: Bulletin of the Polish Academy of Sciences: Technical Sciences. 2021, Vol. 69 Issue 1, p1-5. 5p.

Inconsistencies with formulas for the standard error of the standardized mean difference of repeated measures experiments.

Authors: Kitchenham, Barbara Madeyski, Lech

Source: Statistics in Medicine. 11/30/2020, Vol. 39 Issue 27, p4101-4104. 4p.

A cognitive model for adopting ITIL framework to improve IT services in Indian IT industries.

Authors: Dayal, Rasbihari Vijayakumar, V. Kushwaha, Rahul Chandra et al.

Source: Journal of Intelligent & Fuzzy Systems; 2020, Vol. 39 Issue 6, p8091-8102, 12p

Computer Science vs. COVID-19.

Authors: AFELT, Aneta BYRSKI, Aleksander CALO, Victor et al.

Source: Bulletin of the Polish Academy of Sciences: Technical Sciences. Aug2021, Vol. 69 Issue 4, p1-4. 4p.

Predicting test failures induced by software defects: A lightweight alternative to software defect prediction and its industrial application.

Authors: Madeyski, Lech Stradowski, Szymon

Source: Journal of Systems & Software; May2025, Vol. 223, pN.PAG-N.PAG, 1p

Mutants as Patches: Towards a formal approach to Mutation Testing.

Authors: Lewowski, Tomasz Madeyski, Lech

Source: Foundations of Computing & Decision Sciences; Dec2019, Vol. 44 Issue 4, p379-405, 27p

Would wider adoption of reproducible research be beneficial for empirical software engineering research?

Authors: Madeyski, Lech Kitchenham, Barbara

Source: Journal of Intelligent & Fuzzy Systems; 2017, Vol. 32 Issue 2, p1509-1521, 13p

Addressing mutation testing problems by applying multi-objective optimization algorithms and higher order mutation.

Authors: Quang Vu Nguyen Madeyski, Lech

Source: Journal of Intelligent & Fuzzy Systems; 2017, Vol. 32 Issue 2, p1173-1182, 10p

Impact of pair programming on thoroughness and fault detection effectiveness of unit test suites.

Authors: Madeyski, Lech¹, lech.madeyski@pwr.wroc.pl

Source: Software Process: Improvement & Practice; May/Jun2008, Vol. 13 Issue 3, p281-295, 15p, 10 Charts, 4 Graphs

The impact of hard and easy negative training data on vulnerability prediction performance.

Authors: Al Debeyan, Fahad Madeyski, Lech Hall, Tracy et al.

Source: Journal of Systems & Software; May2024, Vol. 211, pN.PAG-N.PAG, 1p

Bottlenecks in Software Defect Prediction Implementation in Industrial Projects.

Authors: Hryszko, Jarosław Madeyski, Lech

Source: Foundations of Computing & Decision Sciences; Mar2015, Vol. 40 Issue 1, p17-33, 17p