Software development is a collaborative task involving diverse development teams, where toxic communication can negatively impact team mood and project success. Mood surveys enable the early detection of underlying tensions or dissatisfaction within development teams, allowing communication issues to be addressed before they escalate, fostering a positive and productive work environment. The mood can be surveyed indirectly by analyzing the text-based communication of the team. However, emotional subjectivity leads to varying sentiment interpretations across team members; a statement perceived neutrally by one developer might be seen as problematic by another developer with a different conversational culture. Early identification of perception volatility can help prevent misunderstandings and enhance team morale while safeguarding the project.

As software systems grow increasingly complex, explainability has become a crucial non-functional requirement for transparency, user trust, and regulatory compliance. Eliciting explainability requirements is challenging, as different methods capture varying levels of detail and structure. This study examines the efficiency and effectiveness of three commonly used elicitation methods—focus groups, interviews, and online surveys—while also assessing the role of taxonomy usage in structuring and improving the elicitation process. We conducted a case study at a large German IT consulting company, utilizing a web-based personnel management software. A total of two focus groups, 18 interviews, and an online survey with 188 participants were analyzed. The results show that interviews were the most efficient, capturing the highest number of distinct needs per participant per time spent. Surveys collected the most explanation needs overall but had high redundancy. Delayed taxonomy introduction resulted in a greater number and diversity of needs, suggesting that a two-phase approach is beneficial. Based on our findings, we recommend a hybrid approach combining surveys and interviews to balance efficiency and coverage. Future research should explore how automation can support elicitation and how taxonomies can be better integrated into different methods.

Software development is a collaborative task involving different persons. Development team members are often diverse in regard to several aspects, including experience, (soft) skills, and communication habits. Different preferences in what adequate communication looks like influence how communication is perceived and interpreted by team members. In this paper, we investigate differences and similarities in how software developers with varying levels of experience and skills perceive statements from exemplary software project communication. By applying hierarchical cluster analysis on the perception data of 94 software developers, we aim to find groups of developers sharing similar perceptions towards statements from software project communication, and to identify factors that influence this perception. We contribute the following key findings: (1) We statistically identify two groups of software developers whose perceptions differ significantly for about 65% of statements from software project communication; (2) For a logistic regression model, five polarizing statements suffice to assign each participant to their group; (3) Although there is a significant difference in the communication perception, there are no demographic characteristics that differ notably across the two groups. From our results, we conclude that different perceptions of software project communication during collaboration within development teams are a potential risk for the teams’ mood and the project success. We outline how our results can serve use cases like the application of sentiment analysis in software engineering and mindful communication in software teams in general.

Ensuring traceability of safety- and security-related artifacts is vital in software development to comply with standards and mitigate risks. Despite its importance, the practical implementation of defining and tracing safety- and security-relevant artifacts remains ambiguous. Based on eight semi-structured interviews with industry experts, this work explores the definitions, methods, processes, and challenges of tracing safety- and security-related artifacts. The interviews revealed that definitions of safety- and security-relevant artifacts are highly context-dependent, shaped by regulatory standards, internal processes, technical characteristics, and practitioner judgment. Rather than signaling a deficiency, this variability reflects the inherently multifaceted nature of safety and security work, where artifact classification emerges from practical reasoning rather than strict or universal criteria. Tools play a key role in supporting traceability, and cross-team alignment remains a concern in practice. Our findings provide actionable insights for organizations seeking to strengthen traceability. The recommendations encourage the development of internal classification criteria, support effective collaboration with external partners, support guidance, onboarding, and training, and help align practices with across teams, fostering more reliable and transparent management of safety- and security-relevant artifacts.

Lai and Chan [ Computer Vis. Image Underst., 115 (2011), pp. 1647--1661] introduced an analogue of the total variation image reconstruction approach of Rudin, Osher, and Fatemi [ Phys. D, 60 (1992), pp. 259--268] for images on smooth surfaces. The problem is defined in terms of quantities intrinsic to the surface and is therefore independent of the parametrization. In this paper, a rigorous analytical framework is developed for this model and its Fenchel predual. It is shown that the predual of the total variation problem is a quadratic optimization problem for the predual vector field ${q} \in {H}(\operatorname{div};S)$ with pointwise inequality constraints on the surface. As in the flat case, ${q}$ serves as an edge detector. A function space interior-point method is proposed for the predual problem, which is discretized by conforming Raviart--Thomas finite elements on a triangulation of the surface. Well-posedness of the barrier problems is established. Numerical examples including denoising and inpainting problems with both gray-scale and color images on scanned three-dimensional geometries of considerable complexity are presented.

The design and implementation of a dependable system that provides a composition and execution environment for distributed applications whose executions could span arbitrarily large durations is described. The objective is to create a framework for complex service provisioning. By complex service provisioning we primarily mean the ability to compose a given service out of existing ones as well as the ability to exercise dynamic control over the execution of the service. The approach taken is centred around building middleware services based on integration of workflow and agent technologies. The platform enables these two systems to interact via CORBA services. Service behaviour and service deployment are represented as workflow processes. Individual tasks that make up the workflow would be legacy applications, specially created tasks, and agent applications. Agents are able to create workflow instances, receive results from workflow and send inputs to workflows. This enables agents to act as user agents capable of managing workflows on behalf of users.

Production of reliable and flexible distributed applications is a growing area of interest and research. Various middleware technologies are often used as the communication infrastructure and as a practical ease to the network programming problem. Among them, message-oriented middleware (MOM) are known to provide reliable and flexible communication through asynchronous message passing. This kind of middleware is of particular interest when coordinating components that are not designed for simultaneous execution. Usually MOM focus on the communication layer with a programming interface, charge to the external components to adapt to the MOM communication model. We introduce a distributed programming model based on autonomous software entities called agents. Agents act as the glue software components and they offer reliable and flexible properties like atomic execution or migration from node to node. The combination of both a MOM and agents has been implemented in the AAA platform presented in the second part of the paper.

Good user interfaces are very costly to implement and maintain. As user interfaces become more advanced, moving to various forms of direct manipulation, they become even more expensive and difficult to implement. In the recent past, many user interface management systems and related tools for the rapid development of user interfaces have been developed. Some have been successful at reducing interface development costs for some styles of interface, but none fully address the requirements of advanced direct manipulation interfaces. We claim this is because they are founded on basic models and components that work only for simpler interaction styles. We present Tube, a tool for the rapid development of advanced direct manipulation user interfaces, describe its structure, and show how it differs from, and is better than, traditional structures.