Automated Software Measurement Strategies Elaboration Using Unsupervised Learning Data Analysis-Reference-Cited by-同舟云学术

Automated Software Measurement Strategies Elaboration Using Unsupervised Learning Data Analysis

Published:2020 Issue: Volume: Page:341-363
ISSN:1865-0929
Container-title:Communications in Computer and Information Science
language:
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Author:

Dahab Sarah A.^ORCID,Maag Stephane^ORCID

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-40223-5_17

Reference29 articles.

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3. Carvallo, J.P., Franch, X.: Extending the ISO/IEC 9126–1 quality model with non-technical factors for COTS components selection. In: Proceedings of the 2006 International Workshop on Software Quality, WoSQ 2006, pp. 9–14. ACM, New York (2006). https://doi.org/10.1145/1137702.1137706

4. Dahab, S., Porras, J.J.H., Maag, S.: A novel formal approach to automatically suggest metrics in software measurement plans. In: 2018 13th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE). IEEE (2018)

5. Dahab, S.A., Maag, S.: Suggesting software measurement plans with unsupervised learning data analysis. In: ENASE, pp. 189–197. SciTePress (2019)