The field of software development and maintenance is witnessing a significant shift towards AI-driven approaches. The integration of large language models (LLMs) and human expertise is becoming increasingly important in tackling challenges such as reliability, security, and quality. Notable trends include the development of tools and frameworks that analyze commit messages, extract developer rationale, and predict bugs. These advancements have the potential to improve the efficiency, scalability, and trustworthiness of software development processes. Noteworthy papers include:

• Application Modernization with LLMs, which proposes a framework that leverages LLMs for code reasoning and generation, and demonstrates its utility through a real-world case study.
• Automated Extraction and Analysis of Developer's Rationale in Open Source Software, which presents an automated approach for rationale analysis based on pre-trained models and large language models, and shows its feasibility using the OOM-Killer module of the Linux Kernel project.