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Generative AI enables rapid ``vibe coding," where natural language prompts yield working software systems. While this lowers barriers to software creation, it also collapses the boundary between prototypes and engineered software, leading…
Generative Artificial Intelligence (GenAI) is rapidly gaining momentum in software modeling education, embraced by both students and educators. As GenAI assists with interpreting requirements, formalizing models, and translating students'…
The continuing, explosive developments in generative artificial intelligence (GenAI), built on large language models and related algorithms, has led to much excitement and speculation about the potential impact of this new technology.…
The software development workplace poses numerous technical and collaborative accessibility challenges for blind and low vision software professionals (BLVSPs). Though Generative AI (GenAI) is increasingly adopted within the software…
Generative AI models are capable of performing a wide variety of tasks that have traditionally required creativity and human understanding. During training, they learn patterns from existing data and can subsequently generate new content…
Context: As generative AI (GenAI) tools such as ChatGPT and GitHub Copilot become pervasive in education, concerns are rising about students using them to complete rather than learn from coursework-risking overreliance, reduced critical…
Generative AI brings novel and impressive abilities to help people in everyday tasks. There are many AI workflows that solve real and complex problems by chaining AI outputs together with human interaction. Although there is an undeniable…
Moldable development supports decision-making by making software systems explainable. This is done by making it cheap to add numerous custom tools to your software, turning it into a live, explorable domain model. Based on several years of…
Generative AI (GenAI) is reshaping enterprise architecture work in agile software organizations, yet evidence on its effects remains scattered. We report a systematic literature review (SLR), following established SLR protocols of…
Creativity has always been considered a major differentiator to separate the good from the great, and we believe the importance of creativity for software development will only increase as GenAI becomes embedded in developer tool-chains and…
The use of generative AI (GenAI) tools has fundamentally transformed software development. Central to this shift is prompt engineering, the practice of crafting textual prompts to guide GenAI tools in generating useful content. Although…
UX practitioners face novel challenges when designing user interfaces for machine learning (ML)-enabled applications. Interactive ML paradigms, like AutoML and interactive machine teaching, lower the barrier for non-expert end users to…
As generative AI (GenAI) increasingly permeates design workflows, its impact on design outcomes and designers' creative capabilities warrants investigation. We conducted a within-subjects experiment where we asked participants to design…
Generative AI (GenAI) is transforming creative fields shaping our culture and our heritage. We focus on widespread interactions between clients and (creative) specialists highlighting a change in interaction patterns leading to a shift from…
Investigation of students' perceptions and opinions on the use of generative artificial intelligence (GenAI) in education is a topic gaining much interest. Studies addressing this are typically conducted with large heterogeneous groups, at…
Accessibility forums and, more recently, generative AI tools have become vital resources for blind users seeking solutions to computer-interaction issues and learning about new assistive technologies, screen reader features, tutorials, and…
Model-Based Engineering (MBE) has streamlined software development by focusing on abstraction and automation. The adoption of MBE in Maintenance and Evolution (MBM&E), however, is still limited due to poor tool support and a lack of…
Recent strides in interpretable machine learning (ML) research reveal that models exploit undesirable patterns in the data to make predictions, which potentially causes harms in deployment. However, it is unclear how we can fix these…
Generative, multimodal artificial intelligence (GenAI) offers transformative potential across industries, but its misuse poses significant risks. Prior research has shed light on the potential of advanced AI systems to be exploited for…
Generative Artificial Intelligence (GenAI) tools and models have the potential to re-shape educational needs, norms, practices, and policies in all sectors of engineering education. Empirical data, rather than anecdata and assumptions, on…