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The management of third-party package dependencies is crucial to most technology stacks, with package managers acting as brokers to ensure that a verified package is correctly installed, configured, or removed from an application. Diversity…
In software engineering, different approaches and machine learning models leverage different types of data: source code, textual information, historical data. An important part of any project is its dependencies. The list of dependencies is…
Data generation and analysis is a fundamental aspect of many industries and disciplines, from strategic decision making in business to research in the physical and social sciences. However, data generated using software and algorithms can…
Responsible AI is widely considered as one of the greatest scientific challenges of our time and is key to increase the adoption of AI. Recently, a number of AI ethics principles frameworks have been published. However, without further…
Generative Artificial Intelligence (GenAI) tools for source code generation have significantly boosted productivity in software development. However, they also raise concerns, particularly the risk that developers may rely heavily on these…
Generative AI coding tools are relatively new, and their impact on developers extends beyond traditional coding metrics, influencing beliefs about work and developers' roles in the workplace. This study aims to illuminate developers'…
Process mining is increasingly adopted in modern organizations, producing numerous process models that, while valuable, can lead to model overload and decision-making complexity. This paper explores a multi-criteria decision-making (MCDM)…
In the ever-evolving landscape of Artificial Intelligence (AI), the synergy between generative AI and Software Engineering emerges as a transformative frontier. This whitepaper delves into the unexplored realm, elucidating how generative AI…
Effective ideation requires both broad exploration of diverse ideas and deep evaluation of their potential. Generative AI can support such processes, but current tools typically emphasize either generating many ideas or supporting in-depth…
In order to automate AI research we introduce a full, end-to-end framework, OMEGA: Optimizing Machine learning by Evaluating Generated Algorithms, that starts at idea generation and ends with executable code. Our system combines structured…
Machine learning is an important tool for analyzing high-dimension hyperspectral data; however, existing software solutions are either closed-source or inextensible research products. In this paper, we present cuvis.ai, an open-source and…
The significance and abundance of data are increasing due to the growing digital data generated from social media, sensors, scholarly literature, patents, different forms of documents published online, databases, product manuals, etc.…
Generative AI is reshaping how computing systems are designed, optimized, and built, yet research remains fragmented across software, architecture, and chip design communities. This paper takes a cross-stack perspective, examining how…
AI coding assistants are now widely used in software development. Software developers increasingly integrate AI-generated code into their codebases to improve productivity. Prior studies have shown that AI-generated code may contain code…
Trustworthiness is a central requirement for the acceptance and success of human-centered artificial intelligence (AI). To deem an AI system as trustworthy, it is crucial to assess its behaviour and characteristics against a gold standard…
Advances in generative AI point towards a new era of personalized applications that perform diverse tasks on behalf of users. While general AI assistants have yet to fully emerge, their potential to share personal data raises significant…
AI assistance tools such as ChatGPT, Copilot, and Gemini have dramatically impacted the nature of software development in recent years. Numerous studies have studied the positive benefits that practitioners have achieved from using these…
Generative AI systems such as ChatGPT and Claude are built upon language models that are typically evaluated for accuracy on curated benchmark datasets. Such evaluation paradigms measure predictive and reasoning capabilities of language…
AI governance programmes increasingly rely on natural language prompts to constrain and direct AI agent behaviour. These prompts function as executable specifications: they define the agent's mandate, scope, and quality criteria. Despite…
The security of open-source software repositories is increasingly threatened by next-gen software supply chain attacks. These attacks include multiphase malware execution, remote access activation, and dynamic payload generation.…