About this Research Topic
Software engineering and intelligent systems are two dynamic and interrelated fields that have witnessed significant advancements and transformations in recent years. The convergence of these domains has led to the development of innovative applications and solutions that are shaping various industries, from healthcare and finance to transportation and manufacturing. Despite these advancements, several challenges and questions remain, such as how to effectively integrate artificial intelligence (AI) and machine learning (ML) into traditional software engineering practices, and how to ensure the reliability and scalability of intelligent systems. Recent studies have shown promising results in areas like adaptive software, self-learning algorithms, and the application of big data analytics in software development. However, there is still a need for more comprehensive investigations to address existing gaps, such as the ethical implications of AI in software engineering and the development of standardized methodologies for integrating intelligent systems into various applications.
This Research Topic aims to serve as a platform for researchers and practitioners to share their insights, findings, and innovations in this exciting and rapidly evolving intersection of software engineering and intelligent systems. The main objectives include exploring how AI and ML can be leveraged to improve software development processes, understanding the challenges and opportunities in creating adaptive and self-learning software, and examining the role of data science and big data in enhancing software engineering methodologies. Specific questions to be addressed include: How can AI-driven tools improve software quality and efficiency? What are the best practices for integrating intelligent systems into existing software frameworks? How can ethical considerations be incorporated into the development of intelligent software systems?
To gather further insights in the intersection of software engineering and intelligent systems, we welcome articles addressing, but not limited to, the following themes:
- AI in Software Development
- Adaptive and Self-Learning Software
- Data Science and Big Data in Software Engineering
- Software Engineering Methodologies
- Artificial Intelligence and Machine Learning
- Case Studies and Industry Applications
Extended versions of work presented at the “Austrian Conference on Research at Universities of Applied Sciences (FHK Konferenz 2024)” are particularly welcome to submit to this journal. Extended versions should have at least 30% novel content.
This Research Topic aims to serve as a platform for researchers and practitioners to share their insights, findings, and innovations in this exciting and rapidly evolving intersection of software engineering and intelligent systems. The main objectives include exploring how AI and ML can be leveraged to improve software development processes, understanding the challenges and opportunities in creating adaptive and self-learning software, and examining the role of data science and big data in enhancing software engineering methodologies. Specific questions to be addressed include: How can AI-driven tools improve software quality and efficiency? What are the best practices for integrating intelligent systems into existing software frameworks? How can ethical considerations be incorporated into the development of intelligent software systems?
To gather further insights in the intersection of software engineering and intelligent systems, we welcome articles addressing, but not limited to, the following themes:
- AI in Software Development
- Adaptive and Self-Learning Software
- Data Science and Big Data in Software Engineering
- Software Engineering Methodologies
- Artificial Intelligence and Machine Learning
- Case Studies and Industry Applications
Extended versions of work presented at the “Austrian Conference on Research at Universities of Applied Sciences (FHK Konferenz 2024)” are particularly welcome to submit to this journal. Extended versions should have at least 30% novel content.
Keywords: Software Engineering, Artificial Intelligence, Intelligent Systems, Data Science, Machine Learning
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
