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Research Article

Recursive approach for multiple step-ahead software fault prediction through long short-term memory (LSTM)

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References

  • Hoang Pham, System Software Reliability, London, Springer, (2006).
  • G. L. Saini, Deepak Panwar, Sandeep Kumar and Vijander Singh, A systematic literature review and comparative study of different software quality models, Journal of Discrete Mathematical Sciences and Cryptography 23.2, pp. 585-593, (2020). doi: 10.1080/09720529.2020.1747188
  • Vinita Malik and Sukhdip Singh, Artificial intelligent environments: Risk management and quality assurance implementation, Journal of Discrete Mathematical Sciences and Cryptography 23.1, pp. 187-195, (2020). doi: 10.1080/09720529.2020.1721883
  • B. Penzenstadler, A. Raturi, D. Richardson and B. Tomlinson, Safety, Security, Now Sustainability: The Nonfunctional Requirement for the 21st Century, IEEE Software 31.3, pp. 40-47, (2014). doi: 10.1109/MS.2014.22
  • C. Calero, A. Moraga and F. Garcia, Software, Sustainability, and UN Sustainable Development Goals, IT Professional 24.1, pp. 41-48, (2022). doi: 10.1109/MITP.2021.3117344
  • A. Li and H. Pham, A generalized Software Reliability Growth Model with consideration of the uncertainty of operating environments, IEEE Access 7, pp. 84253-84267, (2019). doi: 10.1109/ACCESS.2019.2924084
  • M. A. Levin, T. T. Kalal and J. Rodin, Improving Product Reliability and Software Quality: Strategies, Tools, Process and Implementation, Wiley, (2019).
  • O. I. Abiodun, A. Jantan and A. E. Omolara, Comprehensive review of Artificial Neural Network applications to pattern recognition, IEEE Access 07, pp. 158820-158846, (2019). doi: 10.1109/ACCESS.2019.2945545
  • A. Sherstinsky, Fundamentals of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) network, Physica D: Nonlinear Phenomena 404 (2020). doi: 10.1016/j.physd.2019.132306
  • M. Begum and T. Dohi, A Neuro-Based software fault prediction with Box-Cox Power Transformation, Journal of Software Engineering 10.3, pp. 288-309, (2017).
  • M. Begum, S. B. Hafiz, J. Islam and M. J. Hossain, Long-term software fault prediction with Robust Prediction Interval Analysis via Refined Artificial Neural Network (RANN) Approach, Engineering Letters 29.3 (2021).
  • J. Chi, K. Honda and H. e. a. Washizaki, Defect analysis and prediction by applying the multistage Software Reliability Growth Model, 8th International Workshop on Empirical Software Engineering in Practice (IWESEP), Tokyo, (2017).
  • Vishal Pradhan, Ajay Kumar, and Joydip Dhar, Enhanced growth model of software reliability with generalized inflection S-shaped testing-effort function, Journal of Interdisciplinary Mathematics 25.1 pp. 137-153, (2022). doi: 10.1080/09720502.2021.2006329
  • Deepak Sharma and Pravin Chandra, Linear regression with factor analysis in fault prediction of software, Journal of Interdisciplinary Mathematics 23.1 pp. 11-19, (2020). doi: 10.1080/09720502.2020.1721641
  • A. Tealab, Time series forecasting using artificial neural networks methodologies: A systematic review, Future Computing and Informatics Journal 03.2, pp. 334-340, (2018). doi: 10.1016/j.fcij.2018.10.003
  • R. Islam, N. Akhtar and M. Begum, Long short-term memory (LSTM) networks based software fault prediction using data transformation methods, 2022 International Conference on Advancement in Electrical and Electronic Engineering (ICAEEE), pp. 1-6, (2022).
  • Md Asraful Haque and Nesar Ahmad, An effective software reliability growth model, Safety and Reliability 40.4, pp. 209-220, (2021). doi: 10.1080/09617353.2021.1921547
  • J. Cao, Z. Li and J. Li, Financial time series forecasting model based on CEEMDAN and LSTM, Physica A: Statistical Mechanics and its Applications 519, pp. 127-139, (2019). doi: 10.1016/j.physa.2018.11.061
  • S. Siami-Namini, N. Tavakoli and A. Siami Namin, A Comparison of ARIMA and LSTM in Forecasting Time Series, 17th IEEE International Conference on Machine Learning and Applications (ICMLA) Orlando, (2018).
  • Sima Siami-Namini, Neda Tavakoli, and Akbar Siami Namin, A comparative analysis of forecasting financial time series using arima, lstm, and bilstm, arXiv preprint arXiv:1911.09512 (2019).
  • L. Michael R, Handbook of software reliability engineering, Los Alamitos: IEEE computer society press 222 (1996).
  • Okamura, Hiroyuki and T. Dohi, SRATS: Software reliability assessment tool on spreadsheet (Experience report), IEEE 24th International Symposium on Software Reliability Engineering (ISSRE). IEEE, (2013).

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