The field of software development and scientific research is undergoing a significant transformation with the increasing adoption of Artificial Intelligence (AI) and Generative AI (GenAI) tools. The trend is shifting towards the use of modern programming languages, open-source codes, and modular software, with a growing preference for AI-powered tools to support development workflows. Researchers are exploring the applications, benefits, and challenges of GenAI in various domains, including software development, scientific research, and education. While GenAI has the potential to revolutionize these fields, it also raises concerns about code quality, copyright disputes, and the need for transparent and responsible AI usage. Noteworthy papers in this area include the study on the impact of GenAI on code expertise models and the development of a novel licensing mechanism for open source training data and generative AI models.
The Evolution of AI in Software Development and Scientific Research
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The State of Computational Science in Fission and Fusion Energy
Code with Me or for Me? How Increasing AI Automation Transforms Developer Workflows
The Impact of Generative AI on Code Expertise Models: An Exploratory Study
Generative AI in Science: Applications, Challenges, and Emerging Questions
Generating Proto-Personas through Prompt Engineering: A Case Study on Efficiency, Effectiveness and Empathy
ESG and the Cost of Capital: Insights from an AI-Assisted Systematic Literature Review
Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity
The Narrative Construction of Generative AI Efficacy by the Media: A Case Study of the Role of ChatGPT in Higher Education
If open source is to win, it must go public
LLMalMorph: On The Feasibility of Generating Variant Malware using Large-Language-Models
Self-Admitted GenAI Usage in Open-Source Software
$\texttt{Droid}$: A Resource Suite for AI-Generated Code Detection
GenAI-Enabled Backlog Grooming in Agile Software Projects: An Empirical Study
Past, Present and Future: Exploring Adaptive AI in Software Development Bots
Artificial Intelligence and Journalism: A Systematic Bibliometric and Thematic Analysis of Global Research
A Review of Generative AI in Computer Science Education: Challenges and Opportunities in Accuracy, Authenticity, and Assessment
Consumer Law for AI Agents
AI, Humans, and Data Science: Optimizing Roles Across Workflows and the Workforce
The Case for Contextual Copyleft: Licensing Open Source Training Data and Generative AI
Detecting LLM-generated Code with Subtle Modification by Adversarial Training