相关论文: On Evidence-based Risk Management in Requirements …
The inherent ambiguity of cause and effect boundaries poses a challenge in evaluating causal event extraction tasks. Traditional metrics like Exact Match and BertScore poorly reflect model performance, so we trained evaluation models to…
Context: Requirements engineering process improvement (REPI) approaches have gained much attention in research and practice. Goal: So far, there is no comprehensive view on the research in REPI in terms of solutions and current state of…
The main focus of the requirements engineering (RE) literature has been on the technical aspects related to the RE projects. Furthermore, research has mainly focused on the specific methods for collecting the requirements for an information…
In today's fast-paced world, accurately monitoring stress levels is crucial. Sensor-based stress monitoring systems often need large datasets for training effective models. However, individual-specific models are necessary for personalized…
Systems engineering approaches use high-level models to capture the architecture and behavior of the system. However, when safety engineers conduct safety and reliability analysis, they have to create formal models, such as fault-trees,…
We develop new methods to integrate experimental and observational data in causal inference. While randomized controlled trials offer strong internal validity, they are often costly and therefore limited in sample size. Observational data,…
This paper proposes risk-averse and risk-agnostic formulations to robust design in which solutions that satisfy the system requirements for a set of scenarios are pursued. These scenarios, which correspond to realizations of uncertain…
Resilience has emerged as a crucial concept for evaluating structural performance under disasters because of its ability to extend beyond traditional risk assessments, accounting for a system's ability to minimize disruptions and maintain…
[Background.] Empirical research in requirements engineering (RE) is a constantly evolving topic, with a growing number of publications. Several papers address this topic using literature reviews to provide a snapshot of its "current" state…
Most existing sensor-based monitoring frameworks presume that a large available labeled dataset is processed to train accurate detection models. However, in settings where personalization is necessary at deployment time to fine-tune the…
Performance evaluation of Retrieval-Augmented Generation (RAG) systems within enterprise environments is governed by multi-dimensional and composite factors extending far beyond simple final accuracy checks. These factors include reasoning…
Background: Requirements Changes (RCs) -- the additions/modifications/deletions of functional/non-functional requirements in software products -- are challenging for software practitioners to handle. Handling some changes may significantly…
In the highly interconnected digital landscape of today, safeguarding complex infrastructures against cyber threats has become increasingly challenging due to the exponential growth in the number and complexity of vulnerabilities. Resource…
Context. Nowadays there is a great deal of uncertainty surrounding the effects of experience on Requirements Engineering (RE). There is a widespread idea that experience improves analyst performance. However, there are empirical studies…
Evidence-based practice (EBP) in software engineering aims to improve decision-making in software development by complementing practitioners' professional judgment with high-quality evidence from research. We believe the use of EBP…
[Background] A well-formulated research problem is essential for achieving practical relevance in Software Engineering (SE), yet there is a lack of structured guidance in this early phase. [Aims] Our goal is to introduce and evaluate seven…
Recent advances in learning techniques have garnered attention for their applicability to a diverse range of real-world sequential decision-making problems. Yet, many practical applications have critical constraints for operation in real…
Recent works in relation extraction (RE) have achieved promising benchmark accuracy; however, our adversarial attack experiments show that these works excessively rely on entities, making their generalization capability questionable. To…
[Context]: Companies are increasingly recognizing the importance of automating Requirements Engineering (RE) tasks due to their resource-intensive nature. The advent of GenAI has made these tasks more amenable to automation, thanks to its…
The integration of AI for Requirements Engineering (RE) presents significant benefits but also poses real challenges. Although RE is fundamental to software engineering, limited research has examined AI adoption in RE. We surveyed 55…