arXiv subjects

Thayssa Rocha

Publications and source records attributed to Thayssa Rocha.

6 recordsLinked to original sources

arXiv2026

Design-System-Aware Development with AI: Evaluating Productivity and Design Consistency

Design Systems (DS) help standardize front-end development, yet developers still face challenges when translating high-fidelity mockups into consistent, production-ready interfaces. Although AI-assisted tools have emerged as a potential solution, empirical evidence on their effectiveness within DS-centered workflows remains limited. This paper reports a controlled experiment conducted at a large Brazilian enterprise that compares manual development, DS-only development, and DS-aware AI-assisted development across Angular, iOS, and Android stacks. Results from two experimental cycles show that AI assistance significantly reduced time-to-delivery (by 46.7% to 69.4%), increased task completeness, and decreased performance variability. Analysis of break patterns further suggests reduced workflow friction and smoother task execution. These findings provide empirical evidence that DS-aware AI tools can significantly accelerate development, improve design fidelity, and yield practical benefits for industrial front-end workflows.

cs.SE↗

arXiv2026

Communication Skills in Software Engineering: A Multivocal Review

Communication skills are increasingly recognized as essential in Software Engineering, yet discussions about them remain fragmented across academic and gray literature. This fragmentation is problematic because it limits a broader understanding of how communication is valued, taught, and applied in both educational and professional settings. Through a multivocal literature review, we found strong convergence between academic and gray sources in treating communication as a core competency, while also identifying differences in emphasis, with academia focusing on conceptualization and empirical evidence and gray literature stressing practical consequences and emerging industry practices.

cs.SE↗

arXiv2025

Challenges and Enablers: Remote Work for People with Disabilities in Software Development Teams

The increasing adoption of remote and hybrid work modalities in the technology sector has brought new opportunities and challenges for the inclusion of people with disabilities (PWD) in software development teams (SDT). This study investigates how remote work affects PWDs' experience in mixed-ability SDT, focusing on the unique challenges and strategies that emerge in remote environments. We conducted an online survey with \totalSurveyResponses valid responses, encompassing PWD, their leaders, and teammates, to capture sociotechnical aspects of their experiences with remote collaboration. To deepen our understanding, we carried out 14 structured interviews with software developers who self-identified as having disabilities (six autistic individuals, six with physical disabilities, and two who are d/Deaf). Our analysis combines quantitative data with qualitative coding of open-ended survey responses and interview transcripts. The results reveal that, despite the barriers faced by team members with disabilities, their teammates and leaders have a limited perception of the daily challenges involved in sustaining collaborative remote work. These findings highlight opportunities for improvement in accessibility tools, communication strategies, and adaptive management approaches.

cs.SE↗

arXiv2025

Toward Effective AI Governance: A Review of Principles

Artificial Intelligence (AI) governance is the practice of establishing frameworks, policies, and procedures to ensure the responsible, ethical, and safe development and deployment of AI systems. Although AI governance is a core pillar of Responsible AI, current literature still lacks synthesis across such governance frameworks and practices. Objective: To identify which frameworks, principles, mechanisms, and stakeholder roles are emphasized in secondary literature on AI governance. Method: We conducted a rapid tertiary review of nine peer-reviewed secondary studies from IEEE and ACM (20202024), using structured inclusion criteria and thematic semantic synthesis. Results: The most cited frameworks include the EU AI Act and NIST RMF; transparency and accountability are the most common principles. Few reviews detail actionable governance mechanisms or stakeholder strategies. Conclusion: The review consolidates key directions in AI governance and highlights gaps in empirical validation and inclusivity. Findings inform both academic inquiry and practical adoption in organizations.

cs.SE↗

arXiv2025

Affirmative Hackathon for Software Developers with Disabilities: An Industry Initiative

People with disabilities (PWD) often encounter several barriers to becoming employed. A growing body of evidence in software development highlights the benefits of diversity and inclusion in the field. However, recruiting, hiring, and fostering a supportive environment for PWD remains challenging. These challenges are exacerbated by the lack of skilled professionals with experience in inclusive hiring and management, which prevents companies from effectively increasing PWD representation on software development teams. Inspired by the strategy adopted in some technology companies that attract talent through hackathons and training courses, this paper reports the experience of Zup Innovation, a Brazilian software company, in hosting a fully remote affirmative hackathon with 50 participants to attract PWD developers. This event resulted in 10 new hires and 146 people added to the company's talent pool. Through surveys with participants, we gathered attendees' perceptions and experiences, aiming to improve future hackathons and similar initiatives by providing insights on accessibility and collaboration. Our findings offer lessons for other companies seeking to address similar challenges and promote greater inclusion in tech teams.

cs.SE↗

arXiv2023

Developer Experiences with a Contextualized AI Coding Assistant: Usability, Expectations, and Outcomes

In the rapidly advancing field of artificial intelligence, software development has emerged as a key area of innovation. Despite the plethora of general-purpose AI assistants available, their effectiveness diminishes in complex, domain-specific scenarios. Noting this limitation, both the academic community and industry players are relying on contextualized coding AI assistants. These assistants surpass general-purpose AI tools by integrating proprietary, domain-specific knowledge, offering precise and relevant solutions. Our study focuses on the initial experiences of 62 participants who used a contextualized coding AI assistant -- named StackSpot AI -- in a controlled setting. According to the participants, the assistants' use resulted in significant time savings, easier access to documentation, and the generation of accurate codes for internal APIs. However, challenges associated with the knowledge sources necessary to make the coding assistant access more contextual information as well as variable responses and limitations in handling complex codes were observed. The study's findings, detailing both the benefits and challenges of contextualized AI assistants, underscore their potential to revolutionize software development practices, while also highlighting areas for further refinement.

cs.SE↗