Requirements Engineering (RE) is the pivotal domain within Software Engineering that encompasses the discovery, documentation, and analysis of a system's purpose, grounded in stakeholder needs. In the realm of RE research, we recognize the critical role that quality aspects play in shaping not only what is built but also how requirements are specified. Quality considerations extend to both the system being developed and the requirements themselves. Within this context, the importance of emerging topics such as ethics, privacy, and security in conjunction with traditional quality aspects, such as performance, maintainability, etc., becomes increasingly important. Furthermore, the recent advances in Artificial Intelligence (AI) techniques, and Large Language Models (LLMs) in particular, provide novel opportunities to solve RE tasks, including quality assessment, classification, and tracing. These advancements also pose new challenges for RE, as novel techniques are needed to ensure that AI-based systems are reliable, trustworthy, and exhibit the same degree of quality expected from traditional systems.
This year’s track aims to foster discussion on these key topics:Â
Ethics in Requirements Engineering: Explore the ethical implications and considerations in defining system requirements, ensuring that software development aligns with ethical standards and societal values.
Privacy and Security in Requirements: Address the growing concerns of privacy and security by incorporating robust measures within requirements engineering processes, safeguarding sensitive information and ensuring compliance with data protection regulations.
Emerging Topics in Requirements Engineering:
Large Language Models: Investigate the application of large language models in requirements engineering, exploring their potential to support multiple RE tasks.
AI in RE and RE for AI: Delve into the integration of artificial intelligence (AI) in RE processes, assessing its impact on the discovery, validation, and management of requirements. Devise RE strategies for the support of AI-based system development.
Analysis of Novel Sources: Explore innovative approaches to requirements gathering, including the analysis of app reviews, issue tracking systems, interviews, diagrams, etc., to extract valuable insights and improve the requirements engineering process.
RE for Emerging Societal Challenges: Includes RE techniques for supporting, aging of societies, supporting reskilling and workforce retraining, political bias in media and social media, supporting mental health issues
Additional topics of interest belong to the whole RE realm and are:
Requirements engineering in relation to quality requirementsÂ
Requirements elicitation, analysis and documentation
Requirements verification and validation
Requirements management: evolution, traceability, prioritization, and negotiation
Requirements for particular application domains
Strategies, methods and processes for assuring the quality of requirements
Alignment of requirements to information need/business goals and processes
Risk management in the context of REÂ
Requirements-based project management and cost estimation
Human, social, cultural, and cognitive factors in RE
Regulatory compliance to functional and non-functional requirements
Contemporary RE processes and tools for quality requirements
Chairs: Â Oliver Karras (Leibniz Information Centre for Science and Technology, Germany), Giovanna Broccia (ISTI/CNR, Italy)
Program Committee:Â
TBA
Oliver Karras received his PhD from Leibniz Universität Hannover. He is Head of Curation & Community Building Department for Program Area D – Open Research Knowledge Graph (ORKG) at TIB – Leibniz Information Centre for Science and Technology and Leibniz Universität Hannover. His research focuses on the development of the ORKG and its application across diverse disciplines, including computer science, engineering sciences, energy system research, and medicine. His focus is on the human-centered, neuro-symbolic knowledge organization to improve the availability, discoverability, and accessibility of scientific data, information, and knowledge for humans and machines.
Giovanna Broccia received her PhD in Computer Science from the University of Pisa. Her current research interests lie into different areas, including User-centred aspects in software engineering (e.g. understandability, learnability, users acceptance, cognition), Empirical software engineering and empirical formal methods, Requirements engineering and the use of formal methods in different application domains such as HCI, medical imaging field, and cognitive science.