Related papers: Towards Artefact-based Requirements Engineering fo…
Processing regulations and resulting requirements to achieve regulatory compliance in software engineering (SE) is a developing challenge due to the continuously growing amount, complexity, and expanding scope of regulations. Despite the…
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…
Growing concerns around the trustworthiness of AI-enabled systems highlight the role of requirements engineering (RE) in addressing emergent, context-dependent properties that are difficult to specify without structured approaches. In this…
The various influences in the processes and application domains make Requirements Engineering (RE) inherently complex and difficult to implement. In general, we have two options for establishing an RE approach: we can either establish an…
Background: Nowadays, regulatory requirements engineering (regulatory RE) faces challenges of interdisciplinary nature that cannot be tackled due to existing research gaps. Aims: We envision an approach to solve some of the challenges…
Context: Regulatory acts are a challenging source when eliciting, interpreting, and analyzing requirements. Requirements engineers often need to involve legal experts who, however, may often not be available. This raises the need for…
Machine learning (ML) is used increasingly in real-world applications. In this paper, we describe our ongoing endeavor to define characteristics and challenges unique to Requirements Engineering (RE) for ML-based systems. As a first step,…
Most requirements engineering (RE) process improvement approaches are solution-driven and activity-based. They focus on the assessment of the RE of a company against an external norm of best practices. A consequence is that practitioners…
Large Language Models (LLMs) depend on high-quality, domain-specific natural language datasets. This dependency is particularly pronounced in Requirements Engineering (RE), where core activities rely on textual artifacts such as…
Requirement Engineering (RE) is the foundation of successful software development. In RE, the goal is to ensure that implemented systems satisfy stakeholder needs through rigorous requirements elicitation, validation, and evaluation…
[Context] Artificial intelligence (AI) components used in building software solutions have substantially increased in recent years. However, many of these solutions focus on technical aspects and ignore critical human-centered aspects.…
This paper identifies and tackles the challenges of the requirements engineering discipline when applied to development of AI-based complex systems. Due to their complex behaviour, there is an immanent need for a tailored development…
Artificial Intelligence is increasingly introduced into systems engineering activities, particularly within requirements engineering, where quality assessment and validation remain heavily dependent on expert judgment. While recent AI tools…
Applying Design Science Research (DSR) methodology is becoming a popular working resource for most Information Systems (IS) and Software engineering studies. The research and/or practical design problems that must be faced aim to answer the…
[Context] In traditional software systems, Requirements Engineering (RE) activities are well-established and researched. However, building Artificial Intelligence (AI) based software with limited or no insight into the system's inner…
Requirements Engineering (RE) is a critical phase in software development including the elicitation, analysis, specification, and validation of software requirements. Despite the importance of RE, it remains a challenging process due to the…
Context and motivation. Requirements Engineering (RE) quality still lacks empirical evidence on how specific requirement defects affect downstream activities. Problem: However, empirical data on the detailed effects of requirements quality…
Analysis and design phases are the most crucial part of the software development life-cycle. Reusing the artifacts of these early phases is very beneficial to improve the productivity and software quality. In this paper we analyze the…
Artefacts play a vital role in software and systems development processes. Other terms like documents, deliverables, or work products are widely used in software development communities instead of the term artefact. In the following, we use…
Specifying data requirements for machine learning (ML) software systems remains a challenge in requirements engineering (RE). This vision paper explores causal modelling as an RE activity that allows the systematic integration of prior…