FOFS: Firefly Optimization for Feature Selection to Predict Fault-Prone Software Modules-Reference-Cited by-同舟云学术

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FOFS: Firefly Optimization for Feature Selection to Predict Fault-Prone Software Modules

Published:2021-11-14 Issue: Volume: Page:479-487
ISSN:2367-3370
Container-title:Data Engineering for Smart Systems
language:
Short-container-title:

Author:

Goyal Somya

Publisher

Springer Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-16-2641-8_46

Reference20 articles.

1. NASA (2015) https://www.nasa.gov/sites/default/files/files/Space_Math_VI_2015.pdf

2. Goyal S, Bhatia PK (2021) Empirical software measurements with machine learning. Computational intelligence techniques and their applications to software engineering problems. CRC Press, Boca Raton, pp 49–64. https://doi.org/10.1201/9781003079996

3. Goyal S, Parashar A (2018) Machine learning application to improve COCOMO model using neural networks. Int J Inform Technol Comput Sci (IJITCS) 10(3):35–51. https://doi.org/10.5815/ijitcs.2018.03.05

4. Goyal S, Bhatia PK (2019) A non-linear technique for effective software effort estimation using multi-layer perceptrons, In: Proceedings of international conference on machine learning, big data, cloud and parallel computing (COMITCon). IEEE, pp 1–4. https://doi.org/10.1109/COMITCon.2019.8862256

5. Goyal S, Bhatia P (2020) Comparison of machine learning techniques for software quality prediction. Int J Knowl Syst Sci (IJKSS) 11(2):21–40. https://doi.org/10.4018/IJKSS.2020040102

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