The integration of Generative AI (GenAI) into Architecture, Engineering, and Construction (AEC) design marks a paradigm shift, yet empirical studies on AEC professional adoption are scarce. This study aims to bridge this gap through a mixed-methods study involving interviews with 20 professionals and a survey of 191 professionals. Findings show GenAI is mainly used in conceptual design, improving client and intra-team collaboration, especially in concept-only projects, strong site integration projects, and challenging client engagements projects for inspiration exploration, client communication and design service boundaries expansion. We further uncover a critical paradox: professionals perceive GenAI’s creativity as intrinsically linked to the unpredictability. Additionally, a nuanced “shame-yet-pride” dynamic is identified, wherein professionals publicly regard GenAI as a key asset but conceal its use to exaggerate manual effort. Based on these insights, we recommend fostering an industry-wide discussion for a mindset shift toward transparent collaboration with GenAI. This study offers the first comprehensive empirical study for understanding GenAI’s current role and future potential in transforming AEC design practices.

The transition from conceptual sketch to 3D model poses a major challenge in engineering design. While Mixed Reality (MR) enables direct 3D creation, designers face two key challenges: the Initiation Challenge (lack of meaningful starting points) and the Expression Challenge (difficulty in precise mid-air sketching). We introduce GenerativeSurface, leveraging AI to translate natural language descriptions into interactive 3D surfaces that aid designers in 3D sketching, simultaneously addressing both challenges. Our system transforms the design workflow into a fluid "describe, generate, sketch, iterate" cycle. Comparative evaluation against primitive scaffolding and freehand mid-air sketching demonstrates that our approach effectively bridges the gap between designers' conceptual intent and 3D sketch expression in immersive environments.

Requirements workshop for software stakeholders is the major approach for collecting software requirements. Given the success of AI (Artificial Intelligence), especially NLP (Natural Language Processing) and the recent LLMs (Large Language Models), it is becoming increasingly popular for requirements engineers to use cloud-based AI services to automate the process of requirements documentation based on manually or AI generated meeting minutes either during or after the requirements workshop. However, using cloud-based AI services to process audio recordings of the requirements workshop may introduce many issues such as data privacy, high demand for computational resources and bandwidth, and large latency which make collaboration not efficient. To address these issues, we propose Edge4RE, a novel privacy-aware edge-cloud collaborative framework to support automated software requirements documentation from automated audio recordings during the requirements workshop. Specifically, with our solution, automated audio recordings are first transcribed and segmented into sentences on the local edge device. The edge device applies a lightweight Transformer based classifier fine-tuned using Low Rank Adaptation (LoRA) to identify requirement-related sentences. Afterwards, only requirement-related sentences are sent to the cloud-based LLM to generate the structured requirements documentation. Experimental results demonstrate that our framework can achieve high-quality requirement documentation based on automated audio recordings while reducing latency and bandwidth consumption with privacy protection.

Accessibility is a crucial concept in Virtual Reality (VR), pivotal for meeting the needs of users, including those with disabilities.In recent years, there has been an increasing focus of VR products on enhancing the accessibility of a diverse range of digital content.Despite this growing attention from the VR community, there is a serious lack of empirical research on how VR practitioners consider VR accessibility.This includes their understanding of and insights into VR accessibility challenges and practices in the VR software development life cycle.In this paper, we aim to address these gaps using a mixed-methods approach.Specifically, we conducted interviews with 21 VR practitioners (incl.3D modelers, developers, technical directors, and product managers) and surveyed 202 VR practitioner respondents from VR-related industries.Our findings outline the insights and challenges they face concerning VR accessibility practices in the software development life cycle.Furthermore, our findings shed light on the challenges faced by practitioners concerning VR accessibility and the reasons why it often goes unconsidered.As far as we know, this is the first comprehensive report about the understanding of accessibility in the VR software development life cycle from practitioners' perspectives.We hope this paper will help VR practitioners better understand the practices, challenges, and potential solutions related to VR accessibility.

Context: Personas are commonly employed in software projects to better understand end-users needs. Despite their frequent usage, there is a limited understanding of their practical application and effectiveness. Objective: This paper aims to investigate the current practices, methods, and challenges associated with using personas in software development. Methods: A two-step investigation was conducted, comprising interviews with 26 software developers, UI/UX designers, business analysts, and product managers, along with a survey of 203 practitioners. Results: The findings reveal variations in the frequency and effectiveness of personas across different software projects and IT companies. Additionally, the study highlights the challenges practitioners face when using personas and the reasons for not using them. Notably, the research shows that some human aspects (e.g., the needs of users with disabilities), often assumed to be a key feature of personas, are frequently not considered for various reasons in requirements engineering. Conclusions: The study provides actionable insights for practitioners to overcome challenges in using personas during the requirements engineering stages. Furthermore, it identifies areas for future research to enhance the effectiveness of personas in software development.

People who use software applications are different, including with significant cognitive differences such as neurodiversity. Capturing requirements for software that addresses these cognitive differences is hard for software engineers, especially when they do not have the same cognitive challenges. We wanted to explore the use of virtual reality (VR) in assisting software engineers to better understand the perspectives of the end user for the purpose of human-centric requirements elicitation, with a focus on users with attention-deficit/hyperactivity disorder (ADHD). We developed an immersive VR prototype using a virtual gym environment and fitness app as a concrete motivating example scenario. We carried out an evaluation of requirements identification for ADHD fitness app users by instructing participants to complete activities whilst under visual and auditory distractions similar to various documented symptoms of ADHD. Results indicated an increase in understanding the perspectives of someone with ADHD and an awareness of potential challenges with software not intentionally designed for ADHD users. Improved requirements for our target fitness app resulted that better take into account these diverse user needs.

Requirements engineering (RE) plays a crucial role in developing software systems by bridging the gap between stakeholders' needs and system specifications. However, effective communication and elicitation of stakeholder requirements can be challenging, as traditional RE methods often overlook emotional cues. This paper introduces a multi-modal emotion recognition platform (MEmoRE) to enhance the requirements engineering process by capturing and analyzing the emotional cues of stakeholders in real-time. MEmoRE leverages state-of-the-art emotion recognition techniques, integrating facial expression, vocal intonation, and textual sentiment analysis to comprehensively understand stakeholder emotions. This multimodal approach ensures the accurate and timely detection of emotional cues, enabling requirements engineers to tailor their elicitation strategies and improve overall communication with stakeholders. We further intend to employ our platform for later RE stages, such as requirements reviews and usability testing. By integrating multi-modal emotion recognition into requirements engineering, we aim to pave the way for more empathetic, effective, and successful software development processes. We performed a preliminary evaluation of our platform. This paper reports on the platform design, preliminary evaluation, and future development plan as an ongoing project.

Personas are crucial in software development processes, particularly in agile settings. However, no effective tools are available for generating personas from user feedback in agile software development processes. To fill this gap, we propose a novel tool that uses the GPT-4 model and knowledge graph to generate persona templates from well-processed user feedback, facilitating requirement analysis in agile software development processes. We developed a tool called PersonaGen. We evaluated PersonaGen using qualitative feedback from a small-scale user study involving student software projects. The results were mixed, highlighting challenges in persona-based educational practice and addressing non-functional requirements.