Assessing the Software Developer’s Quality Using Fuzzy Estimates-Reference-Cited by-同舟云学术

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Assessing the Software Developer’s Quality Using Fuzzy Estimates

Published:2018-12-07 Issue: Volume: Page:203-212
ISSN:2194-5357
Container-title:Advances in Intelligent Systems and Computing
language:
Short-container-title:

Author:

Afanasieva Tatiana,Moiseev Vlad

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-01818-4_20

Reference11 articles.

1. Mockus, A.: Software support tools and experimental work. In: Basili, V., et al. (eds.): Empirical Software Engineering Issues: Critical Assessments and Future Directions. LNCS, vol. 4336, pp. 91–99. Springer, Heidelberg (2007)

2. Cosentino, V., Luis, J., Cabot J.: Findings from GitHub: methods, datasets and limitations. In: Proceedings of 2016 IEEE/ACM 13th Working Conference on Mining Software Repositories, MSR 2016, 14–15 May 2016, Austin, TX, USA (2016). https://doi.org/10.1145/2901739.2901776

3. Altinger, H., Siegl, S., Dajsurent, Y., Wotawa, F.: A novel industry grade dataset for fault prediction based on model-driven developed automotive embedded software. In: Proceedings of 12th Working Conference on Mining Software Repositories 2015, At Florence, Italy, MSR 2015 (2015). https://doi.org/10.1109/msr.2015.72

4. McCabe, T.J.: A complexity measure. IEEE Trans. Softw. Eng. 4, 308–320 (1976)

5. Halstead, M.H.: Elements of Software Science (Operating and Programming Systems Series). Elsevier Science Inc., New York (1977)

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1. Models and Methods for Searching Cohesive Teams of Software Developers;Artificial Intelligence in Models, Methods and Applications;2023

2. Fuzzy Rating System for Cohesive Development Teams;Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation;2021-08-24

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