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February 6, 2026Iranian Journal of Science and Technology Transactions of Electrical Engineering

Software Fault Prediction in Service-Oriented Architecture Using Deep Learning Enabled Adaptive Optimization Technique

Raghuraj Singh Kuldeep Kumar

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Key Points

The study reveals improvements in software fault prediction accuracy, enhancing overall system reliability.
Key evidence includes a significant performance boost in predictive analytics with deep learning techniques.
Analysis using deep learning and adaptive optimization techniques indicates a promising approach for fault prediction.
This finding highlights the potential for increased efficiency in service-oriented architecture, encouraging further exploration.

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Implication

Observational analysis uncovers software fault prediction improvements in service-oriented architecture, indicating enhanced reliability.

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Cite This Study

Singh et al. (2026) studied this question.

synapsesocial.com/papers/69a76736badf0bb9e87e0097 https://doi.org/10.1007/s40998-026-01019-0

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