Intelligent Software Engineering: Synergy Between AI and Software Engineering
A special issue of Future Internet (ISSN 1999-5903). This special issue belongs to the section "Internet of Things".
Deadline for manuscript submissions: 20 October 2026 | Viewed by 51
Special Issue Editors
Interests: software intelligent synthesis theory and methods; model-driven development methods; cyber–physical fusion systems; artificial intelligence system testing technology; intelligent algorithm error location and repair technology
Interests: concurrency theory and Petri net theory; model checking and temporal logic; machine learning and multi-agent; discrete event systems and real-time embedded systems; workflow systems; human–machine–object systems; drone collaboration; online transaction fraud detection
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Special Issue Information
Dear Colleagues,
Artificial intelligence (AI)—particularly the technology and methods of machine learning (ML), deep learning (DL), and large language models (LLMs)—has profoundly transformed the landscape of software engineering (SE). Traditional software engineering processes such as requirement analysis, software design, testing, and maintenance are increasingly integrated with intelligent automation, enabling more adaptive, efficient, and human–machine collaborative workflows. This synergy between AI and SE has laid the foundation for intelligent software engineering (ISE), where AI not only assists developers but also actively participates in software reasoning, synthesis, and evolution.
At the same time, the complexity of modern software systems, ranging from cyber–physical systems to distributed cloud services, has grown beyond the capacity of manual engineering processes. Software must now adapt autonomously to evolving environments, uncertain requirements, and dynamic resource constraints. AI techniques such as reinforcement learning, program synthesis, and automated reasoning provide new possibilities for achieving self-adaptive, self-healing, and self-optimizing software. This convergence is redefining the goals of software engineering from static correctness to continuous intelligence, where systems evolve intelligently through experience and data.
Moreover, the emergence of LLMs and foundation models (e.g., GPT, CodeLlama, DeepSeekCoder) has opened unprecedented opportunities for code understanding, automated documentation, bug fixing, and software generation. However, challenges also remain in reliability, interpretability, and human–AI co-development. Bridging these disciplines requires not only technical innovation but also methodological and ethical frameworks that ensure trustworthy, efficient, and maintainable AI-driven software. This Special Issue aims to explore the latest advancements, methodologies, and tools at the intersection of AI and SE, fostering a holistic understanding of how intelligent mechanisms can enhance every stage of the software lifecycle.
This Special Issue will provide a comprehensive forum for disseminating the most recent theoretical, methodological, and practical advances in ISE. It will enhance the connection of researchers in the fields of AI and software engineering, promoting interdisciplinary collaboration and cross-domain innovation.
By consolidating emerging studies on AI-assisted software repair, code synthesis, intelligent testing, and autonomous software evolution, this Special Issue will contribute to the development of next-generation software systems that are more adaptive, robust, and trustworthy. The expected impact includes the following:
- Advancing theory and methodology in AI-driven software developing, analysis, and verification;
- Encouraging reproducible and open research on LLM-based software development tools;
- Promoting the integration of SE4AI and AI4SE paradigms, accelerating intelligent automation in software lifecycles;
- Providing insights for industrial applications such as DevOps automation, software analytics, and digital twins.
Ultimately, this Special Issue seeks to shape the emerging discipline of intelligent software engineering, fostering a deeper synergy between human expertise and AI capabilities.
Original research articles, reviews, and application papers are welcome. Topics of interest include, but are not limited to, the following:
- Automated program synthesis and code generation;
- Intelligent software repair and self-healing mechanisms;
- LLM-based software development and debugging;
- AI-assisted software testing and test case generation;
- Intelligent requirements analysis and specification mining;
- Reinforcement learning for adaptive software optimization;
- Software defect prediction using deep learning models;
- Explainable AI for software engineering decision support;
- Human–AI collaboration in software design and maintenance;
- Knowledge graph-based software reasoning and dependency analysis;
- Intelligent refactoring and performance optimization;
- AI-driven software project management and effort estimation;
- Secure and trustworthy AI for software lifecycle management;
- Multi-agent systems for cooperative software engineering;
- Transfer learning and domain adaptation in software analytics;
- Automated code summarization and documentation generation;
- Data-driven approaches for software quality assessment;
- AI-augmented continuous integration and deployment (CI/CD) pipelines;
- Empirical studies on AI4SE and SE4AI synergy.
Prof. Dr. Yunwei Dong
Prof. Dr. Guanjun Liu
Dr. Xiaomin Wei
Guest Editors
Manuscript Submission Information
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Keywords
- artificial intelligence
- software engineering
- large language models (LLMs)
- software repair
- program synthesis
- machine learning
- automated testing
- software analytics
- intelligent systems
- AI4SE
- SE4AI
- human–AI collaboration
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