Cleidson R. B. de Souza

Manaal Basha, Aimeê M. Ribeiro, Jeena Javahar et al.

Understanding how developers interact with code generation tools (CGTs) requires detailed, real-time data on programming behavior which is often difficult to collect without disrupting workflow. We present \textit{CodeWatcher}, a lightweight, unobtrusive client-server system designed to capture fine-grained interaction events from within the Visual Studio Code (VS Code) editor. \textit{CodeWatcher} logs semantically meaningful events such as insertions made by CGTs, deletions, copy-paste actions, and focus shifts, enabling continuous monitoring of developer activity without modifying user workflows. The system comprises a VS Code plugin, a Python-based RESTful API, and a MongoDB backend, all containerized for scalability and ease of deployment. By structuring and timestamping each event, \textit{CodeWatcher} enables post-hoc reconstruction of coding sessions and facilitates rich behavioral analyses, including how and when CGTs are used during development. This infrastructure is crucial for supporting research on responsible AI, developer productivity, and the human-centered evaluation of CGTs. Please find the demo, diagrams, and tool here: https://osf.io/j2kru/overview.

Jeena Javahar, Tanya Budhrani, Manaal Basha et al.

The use of AI code-generation tools is becoming increasingly common, making it important to understand how software developers are adopting these tools. In this study, we investigate how developers engage with Amazon's CodeWhisperer, an LLM-based code-generation tool. We conducted two user studies with two groups of 10 participants each, interacting with CodeWhisperer - the first to understand which interactions were critical to capture and the second to collect low-level interaction data using a custom telemetry plugin. Our mixed-methods analysis identified four behavioral patterns: 1) incremental code refinement, 2) explicit instruction using natural language comments, 3) baseline structuring with model suggestions, and 4) integrative use with external sources. We provide a comprehensive analysis of these patterns .

Francisco J. Gutierrez, Yazmin Magallanes, Laura S. Gaytán-Lugo et al.

Computer-Supported Cooperative Work, or simply CSCW, is the research area that studies the design and use of socio-technical technology for supporting group work. CSCW has a long tradition in interdisciplinary work exploring technical, social, and theoretical challenges for the design of technologies to support cooperative and collaborative work and life activities. However, most of the research tradition, methods, and theories in the field follow a strong trend grounded in social and cultural aspects from North America and Western Europe. Therefore, it is inevitable that some of the underlying, and established, knowledge in the field will not be directly transferrable or applicable to other populations. This paper presents the results of an interview study conducted with Latin American faculty on the feasability, viability, and prospect of a curriculum proposal for CSCW Education in Latin America: To this end, we conducted nine interviews with faculty currently based in six countries of the region, aiming to understand how a CSCW course targeted to undergraduate and/or graduate students in Latin America might be deployed. Our findings suggest that there are specific traits that need to be addressed in such a course, such as: tailoring foundational CSCW concepts to the diversity of local cultures, motivating the involvement of students by tackling relevant problems to their local communities, and revitalizing CSCW research and practice in the continent.