Software reliability prediction by recurrent artificial chemical link network
Author:
Publisher
Springer Science and Business Media LLC
Subject
Strategy and Management,Safety, Risk, Reliability and Quality
Link
https://link.springer.com/content/pdf/10.1007/s13198-021-01276-8.pdf
Reference40 articles.
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2. Behera AK, Panda M (2019) Software reliability prediction with ensemble method and virtual data point incorporation. International conference on biologically inspired techniques in many-criteria decision making. Springer, Cham, pp 69–77. https://doi.org/10.1007/978-3-030-39033-4_7
3. Behera AK, Nayak SC, Dash CSK, Dehuri S, Panda M (2019) Improving software reliability prediction accuracy using CRO-based FLANN. Innovations in computer science and engineering. Springer, Singapore, pp 213–220. https://doi.org/10.1007/978-981-10-8201-6_24
4. Bhuyan MK, Mohapatra DP, Sethi S (2016) Software reliability assessment using neural networks of computational intelligence based on software failure data. Baltic J Modern Comput 4(4):1016–1037. https://doi.org/10.22364/bjmc.2016.4.4.26
5. Bisi M, Goyal NK (2015) Prediction of software inter-failure times using artificial neural network and particle swarm optimisation models. Int J Soft Eng Technol Appl 1(2–4):222–244. https://doi.org/10.1504/IJSETA.2015.075629
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