Seeking the advantages delivered by agile methods in small-scale software development, large organisations are also adopting agile methods. However, scaling results in a huge growth of socio-technical dependencies that can lead to waiting time, delays, and defects and hinder the teams' ability to recognize their own responsibilities. This research proposes an approach to enable teams' autonomy and clarifies teams' responsibility assignments by aligning socio-technical dependencies. By utilising compile-time, run-time, and task dependencies, our approach identifies the wasteful dependencies between the social structures (teams) and the corresponding technical structures (architecture) and also suggests improvements. The initial results suggest that the approach correctly identifies the wasteful dependencies that are hindering teams' responsibility assignments. The suggested solution proposals are also considered useful. Awareness of such wasteful dependencies is the first step toward being able to handle them successfully. © 2023 IEEE.

Context: In software engineering, snowball sampling has been used as a supplementary and primary search strategy. The current guidelines recommend using Google Scholar (GS) for snowball sampling. However, the use of GS presents several challenges when using it as a source for citations and references. Objective: To compare the effectiveness and usefulness of two leading citation databases (GS and Scopus) for use in snowball sampling search. Method: We relied on a published study that has used snowball sampling as a search strategy and GS as the citation source. We used its primary studies to compute precision and recall for Scopus. Results: In this particular case, Scopus was highly effective with 95% recall and had better precision of 5.1% compared to GS’s 2.8%. Moreover, Scopus found nine additional relevant papers. On average, one would read approximately 15 extra papers in GS than Scopus to identify one additional relevant paper. Furthermore, Scopus supports batch downloading of both citations and papers’ references, has better quality metadata, and does better source filtering. Conclusion: This study suggests that Scopus seems to be more effective and useful for snowball sampling than GS for systematic secondary studies attempting to identify peer-reviewed literature. EVIE © 2022 The Authors.

Contribution: In this study, we accumulated the knowledge and generated evidence on how and in what context CDIO framework has been used in software engineering (SE) education. The aggregated evidence will enable SE academics in making informed decisions while adopting CDIO for SE education and build upon it. Background: CDIO framework is relevant for SE as it focuses on enabling engineering graduates in conceiving, designing, implementing, and operating complex systems and products. We were not able to find any study that identifies and aggregates the evidence on the use of CDIO for SE education. Research Questions: This study attempts to answer the following research questions: 1) how CDIO has been used in SE education? and 2) what are the experiences of academics in applying the CDIO framework in SE education? Methodology: Using a mixed-method approach (systematic mapping study and interview study with experienced academics in SE), we established the state of the art and practice on the use of CDIO in SE education. Findings: Getting a commitment from the higher management, teachers, and students is a major challenge in the adoption of the CDIO initiative followed by a lack of competence, finance, and resources. Ownership, motivation, persistence, and training of teachers and students are required not only to adopt CDIO for SE but also to sustain it.

Software development is a collaborative endeavour. Organisations that develop software assign modules to different teams, i.e., teams own their modules and are responsible for them. These modules are rarely isolated, meaning that there exist dependencies among them. Therefore, other teams might often contribute to developing modules they do not own. The contribution can be, among other types, in the form of code authorship, code review, and issue detection. This research presents a model to investigate the alignment between module ownership and contribution and the preliminary results of an industrial case study to evaluate the model in practice. Our model uses seven metrics to assess teams' contributions. Initial results suggest that the model correctly identifies misalignment between ownership and contribution. The detection of misalignment between ownership and contribution is the first step towards investigating the impact it might have on the faster accumulation of Technical Debt. © 2022 IEEE.

Background: Software development is a knowledge-intensive and creative activity requiring human ingenuity, thus, sustainability from an engineer's perspective (i.e., meeting an engineer's personal and professional needs while maintaining their mental and physical well-being) must be achieved and maintained.

Aims: With this paper, we aim to bring attention to the currently overlooked aspect of sustainability from an individual engineer's perspective.

Method: Through an analysis of systematic literature reviews and mapping studies, this research demonstrates a lack of research investigating the individual (human) dimension of sustainability in the current software engineering literature.

Results: The analysis of the literature reviews reveals that the current research has mainly focused on reducing the energy footprint of software systems. Thus, revealing the renewed need for paying attention to the individual engineer's perspective.

Conclusion: Future research should leverage contributions from related research areas like human aspects in software engineering (e.g., topics like cognition and motivation). There is a need for identifying factors that impact sustainability at an individual level and their interplay with the team and organization level practices, policies, and decisions. The overall ambition is to develop empirically validated guidelines and best practices to measure, improve and maintain sustainability from an engineer's perspective. Such measures are expected to ensure engineers' sustainability and enable highquality software development.