Software Engineering and Machine Learning: Latest Advances and Prospects

Dear Colleagues,

This Special Issue, titled “Software Engineering and Machine Learning: Latest Advances and Prospects”, aims to explore the rapidly evolving intersection of software engineering and machine learning (ML), highlighting methods, tools, and theoretical foundations that enable the development of reliable, efficient, and trustworthy intelligent systems. As ML models are increasingly integrated into critical software systems, new challenges emerge regarding verification, maintainability, adaptability, and ethical compliance.

This Special Issue welcomes original research and review articles that address these challenges from both practical and theoretical perspectives. Topics of interest include, but are not limited to, ML-based software development and testing, assurance for ML components, formal and empirical methods for verifying AI-driven systems, automated software engineering using ML, and human–AI collaboration in software processes. Contributions that focus on safety, security, transparency, robustness, and the operationalisation of ethical requirements in ML-enabled software are particularly encouraged.

By bringing together diverse approaches, this Special Issue aims to foster cross-disciplinary dialogue and advance the state of the art in building dependable and responsible intelligent software systems.

Dr. Sinem Getir Yaman
Guest Editor

Manuscript Submission Information

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