Related papers: Preliminary Guideline for Creating Boundary Artefa…
Foundation models that are capable of automating cognitive tasks represent a pivotal technological shift, yet their societal implications remain unclear. These systems promise exciting advances, yet they also risk flooding our information…
A growing number of empirical software engineering researchers suggest that a complementary focus on theory is required if the discipline is to mature. A first step in theory-building involves the establishment of suitable theoretical…
This research aims to design and develop a new requirements prioritization approach for analyzing and prioritizing stakeholders requirements which are mentioned in the feedback for software products. This paper presents a PhD research…
We consider the problem of learning structures and parameters of Continuous-time Bayesian Networks (CTBNs) from time-course data under minimal experimental resources. In practice, the cost of generating experimental data poses a bottleneck,…
Software architecture knowledge transfer is essential for software development, but related documentation is often incomplete or ambiguous, making oral explanations a common means. Our broader aim is to explore how such explanations might…
We present a framework for uncovering and exploiting dependencies among tools and documents to enhance exemplar artifact generation. Our method begins by constructing a tool knowledge graph from tool schemas,including descriptions,…
Instrumental variables have proven useful, in particular within the social sciences and economics, for making inference about the causal effect of a random variable, B, on another random variable, C, in the presence of unobserved…
Software development relies heavily on text-based communication, making sentiment analysis a valuable tool for understanding team dynamics and supporting trustworthy AI-driven analytics in requirements engineering. However, existing…
Newcomers to a software project must overcome many barriers before they can successfully place their first code contribution, and they often struggle to find information that is relevant to them. In this work, we argue that much of the…
Generative models are increasingly paired with safety classifiers that filter harmful or undesirable outputs. A common strategy is to fine-tune the generator to reduce the probability of being filtered, but this can be suboptimal: it often…
Bundle recommendation aims to suggest a set of interconnected items to users. However, diverse interaction types and sparse interaction matrices often pose challenges for previous approaches in accurately predicting user-bundle adoptions.…
Context: Responsibility gaps, long-recognized challenges in socio-technical systems where accountability becomes diffuse or ambiguous, have become increasingly pronounced in GenAI-enabled software. The generative and adaptive nature…
Empathy is a powerful yet often overlooked element in software engineering (SE), supporting better teamwork, smoother communication, and effective decision-making.This paper introduces 17 actionable empathy guidelines designed to support…
Large language models (LLMs) have facilitated the generation of high-quality, cost-effective synthetic data for developing downstream models and conducting statistical analyses in various domains. However, the increased reliance on…
The use of metrics underpins the quantification, communication and, ultimately, the functioning of a wide range of disciplines as diverse as labour recruitment, institutional management, economics and science. For application of metrics,…
This paper discusses a model-based approach to validate software requirements in agile development processes by simulation and in particular automated testing. The use of models as central development artifact needs to be added to the…
Problem-based visualization research provides explicit guidance toward identifying and designing for the needs of users, but absent is more concrete guidance toward factors external to a user's needs that also have implications for…
This paper introduces BioAgent Bench, a benchmark dataset and an evaluation suite designed for measuring the performance and robustness of AI agents in common bioinformatics tasks. The benchmark contains curated end-to-end tasks (e.g.,…
Requirements Engineering (RE) is a critical discipline mostly driven by uncertainty, since it is influenced by the customer domain or by the development process model used. We aim to investigate RE processes in successful project…
In Software Engineering, early detection of architectural issues is key. It helps mitigate the risk of poor performance, and lowers the cost of repairing these issues. Metrics give a quick overview of the project which helps designers with…