Abstract This research commentary explores how requirements engineering (RE) can contribute to achieving digital humanism in AI-enabled healthcare, ensuring that technological innovation is balanced with human values. Drawing on insights from a panel discussion at the REWBAH’25 (RE for Well-Being, Aging, and Health) workshop, we identify four key themes: the necessity of interdisciplinary collaboration, the nuances of cultural and individual differences, human-AI collaborative decision-making, and the challenge of balancing technological advancement with sustainability and emotional considerations. We argue that RE is well suited for addressing these issues because it brings together diverse stakeholder perspectives to define what systems should achieve and how they should be used. In this paper, we build on digital humanism principles, on RE-relevant frameworks for AI, and on the above themes to frame the role of RE in supporting human-centred healthcare. We highlight open challenges, and outline five promising research directions and related research questions to guide future research and practice in RE, aiming to ensure that AI-enabled healthcare systems better reflect the values of digital humanism.

The purpose of requirements engineering (RE) is to make sure that the expectations and needs of the stakeholders of a software system are met. Emotional needs can be captured as emotional requirements that represent how the end user should feel when using the system. Differently from functional and quality (non-functional) requirements, emotional requirements have received relatively less attention from the RE community. This study is motivated by the need to explore and map the literature on emotional requirements. The study applies the systematic mapping study technique for surveying and analyzing the available literature to identify the most relevant publications on emotional requirements. We identified 34 publications that address a wide spectrum of practices concerned with engineering emotional requirements. The identified publications were analyzed with respect to the application domains, instruments used for eliciting and artefacts used for representing emotional requirements, and the state of the practice in emotion-related requirements engineering. This analysis serves to identify research gaps and research directions in engineering emotional requirements. To the best of the knowledge by the authors, no other similar study has been conducted on emotional requirements.

Mining app stores and social media has proven to be a good source for collecting user feedback to foster requirements engineering and software evolution. Recent literature on mining software-related data from social platforms, such as Twitter and Facebook, shows that it complements app store mining. However, there are many other platforms where users discuss and provide feedback on software applications that are not thoroughly researched and analysed. One of such platforms is reddit. In this paper, we introduce reddit as a new potential data source and explore if and how requirements engineering and software evolution can benefit from obtaining user feedback from reddit. We also present an exploratory study in which we analysed the usage characteristics (i.e., frequency of posts, number of comments, and number of users for each subreddit) of reddit posts about software applications. Furthermore, we examined the content of the posts and the results reveal that almost 54% of posts contain useful information. Finally, we investigated the potential of automatic classification and applied machine learning algorithms to unstructured and noisy reddit data to perform automated classification into the categories of bug reports, feature related, and irrelevant. We found that the Support Vector Machine algorithm with the F1-score of 84% can be effective in categorizing reddit posts. Our results show that reddit posts provide useful feedback on software applications that can foster requirements engineering and software evolution.

The development of large socio-technical systems is now more feasible with the availability of service-oriented cloud computing although this results in a higher complexity level with respect to security and dependability in service-ecosystems. Additionally, the communication between humans and software is more complex too. Developing system architectures that comprise proactive agents are a means to tackle that complexity. However, there is a lack of socio-technical design methods for generating agent-based architectures that get deployed on platforms as a service in Clouds. Such a method must be easy to comprehend and enactable in a pragmatic way. To demonstrate the method, the paper uses a running case based on an emergency healthcare-provision scenario in homes for elderly in sparsely populated areas.

In this paper, we describe research results arising from a technology transfer exercise on agent-oriented requirements engineering with an industry partner. We introduce two improvements to the state-of-the-art in agent-oriented requirements engineering, designed to mitigate two problems experienced by ourselves and our industry partner: (1) the lack of systematic methods for agent-oriented requirements elicitation and modelling; and (2) the lack of prescribed deliverables in agent-oriented requirements engineering. We discuss the application of our new approach to an aircraft turnaround simulator built in conjunction with our industry partner, and show how agent-oriented models can be derived and used to construct a complete requirements package. We evaluate this by having three independent people design and implement prototypes of the aircraft turnaround simulator, and comparing the three prototypes. Our evaluation indicates that our approach is effective at delivering correct, complete, and consistent requirements that satisfy the stakeholders, and can be used in a repeatable manner to produce designs and implementations. We discuss lessons learnt from applying this approach.

We have repeatedly encountered in industry-oriented research projects missing stakeholder input and invalid requirements. This has prompted us to come up with a novel idea to mitigate the problem of collecting and documenting requirements. The essence of the approach proposed by us lies in linking two kinds of artifacts proposed by agent-oriented modeling – goal models and behavioral scenarios – to user stories. In the paper, we first provide short overviews of requirements engineering in agile software development and agent-oriented modeling. We then present our approach of using agent-oriented modeling in agile requirements engineering, and illustrate it with an example from a real-life application. Finally we discuss anecdotal evidence received from this and other real-life projects and set future research directions. The main conclusion from the work performed is that our approach enables simple and lightweight identifying, tracing, and documenting require-

This paper presents experience with using a hybrid agent-oriented software engineering methodology for designing an agent-based software system. We elicit and analyse system requirements using ROADMAP, with associated tool REBEL. We develop initial system design using Prometheus with associated tool PDT. Applying the combination of the methodologies facilitates understanding of system requirements by non-technical clients. A key feature of our work is its handling of quality requirements, which are identified as an essential asset for analysing design alternatives. We contribute to the current state of art by demonstrating the application of a hybrid methodology with a case study of a smart music player. We created concrete artefacts to represent models and found and clarified conflicting concepts between the two methodologies when we developed the case study. Suggestions are proposed to facilitate goal elicitation and verification.

The concepts of COBOL can be well represented by a virtual machine that makes use of descriptors and descriptor lists. The architecture of such virtual machine for COBOL, which supports incremental compilation, is presented in this paper. The structure of different descriptors and descriptor lists of the virtual machine is described. Principles of incremental compilation of COBOL paragraphs are given. The use of stacks for holding temporary values and subprogram parameters is explained. Addressing modes of the virtual machine are discussed, and its instruction set is presented. Options for efficient implementation of the virtual machine on a real machine are discussed.