Abstract While Generative AI (GenAI) has rapidly transformed software development and GenAI tools receive widespread adoption, how humans and AI should collaborate has become a focal point for Agile practitioners, whose values emphasise teamwork and collaboration. Yet, despite growing interest, research on human-AI collaboration in software engineering, especially within Agile contexts, remains limited. Our study investigates Agile practitioners’ perceptions of collaborating with GenAI in software development activities. We conducted a survey with 73 Agile practitioners, revealing how they currently collaborate with GenAI across various activities and how they expect this collaboration to evolve. Key findings include that GenAI is currently not a substantial part of real-world workflows, being either unused or limited to an assistant role, but that there is a clear tendency towards greater AI involvement in the future, with practitioners increasingly viewing AI as a collaborator rather than merely a tool. These findings advance our understanding of human-AI collaboration in Agile settings and can guide both future research and the practical adoption of GenAI in Agile environments.

Abstract The increasing adoption of hybrid and remote work has reshaped how software teams communicate, collaborate, and make design decisions. Our prior study showed that hybrid setups often result in missed discussions, fragmented understanding, and limited documentation of design rationale. At the same time, Generative AI (GenAI) tools–such as GitHub Copilot and ChatGPT–are becoming embedded in development workflows, providing support in code generation. While GenAI’s role in software development is gaining attention, its impact on early-stage design ideation activities and collaboration in hybrid teams remains underexplored. This paper builds on earlier findings to propose a forward-looking vision of GenAI as an instant, readily available co-developer in hybrid software design. We revisit documented challenges from our earlier study on hybrid collaboration and outline how GenAI could address these issues by facilitating asynchronous participation, surfacing undocumented rationale, and preserving design continuity. We present a conceptual framing of GenAI-supported collaboration and propose a research agenda to guide future studies on integrating GenAI into hybrid settings.

Background: Global Software Engineering (GSE) extends geographical, temporal, and cultural boundaries in distributed environments. Over the past two decades, GSE research has evolved to manage software development for distributed teams. The COVID-19 pandemic highlights the need for comprehensive research, particularly during the software design phase, to support team collaboration in distributed development. Aim: This study systematically analyzes the evolution of research emphasis in the GSE field, specifically exploring on whether the research focuses increasing on software design due to the global pandemic. Method: We systematically analyzed the existing literature in two phases. In the first phase of our study, we mapped GSE research over the two decades leading to the pandemic (2000–2020). In the second phase, we used the forward snowballing approach to examine the literature on the software design phase published between 2020 and 2022. Results: The analysis of 592 research studies in the two phases reveals various trends in GSE research. Evaluation research is the most explored research type in methods and processes, and human aspects of development. Despite the paradigm shift caused by the COVID-19 pandemic that increased reliance on distributed teams, results show that while software organizations are extensively studied across all software engineering phases, the software design phase remains one of the least explored areas. Conclusion: This work highlights the evolving GSE research trends, emphasizing the rising significance of collaborative software design in distributed settings. Our findings address current research gaps and underscore the need for further research on software design activities. This contribution envisions a more collaborative, adaptable GSE field, guiding future research to support distributed teams.

Background. Global Software Engineering (GSE) poses several challenges during the software design process. While the existing literature provides practices and guidelines to improve architecture knowledge management in GSE-based software organizations, the challenges related to organizing collaboration during the software design process still need attention. Aim. This study aims to identify the collaboration challenges faced by distributed teams during the software design process and provide recommendations. Method. We conducted semi-structured interviews with eight professionals working in different GSE-based organizations. Results. The study revealed three challenges that underscore the negative impact of the distributed setting on team collaboration during the software design process. Conclusion. We provide recommendations and propose future research direction to enhance team collaboration in the software design process for GSE-based organizations.

Background. Global Software Engineering (GSE) education is an established practice in academia. Several methods and tools support communication and programming activities, but earlier development stages, such as software design and modeling practices, are less explored. Aim. The goal of this work is to analyze the learners’ perspective during an online Software Engineering course. In particular, we focus on planning/organization activities and socio-technical challenges during the software design and modeling process. Method. We used a mixed-method approach to collect data from 30 undergraduate students enrolled in an online Software Engineering course. We combined questionnaires and interviews to analyze four GSE elements (i.e., communication practices, team collaboration, task allocation and distribution, and usage of collaboration tools). Moreover, we analyzed the socio-technical challenges faced by the teams. Results. Brainstorming is the most common practice used for planning so (...).