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Analysing and improving productivity has been one of the main goals of software engineering research since its beginnings. A plethora of studies has been conducted on various factors that resulted in several models for analysis and…
As networking systems become increasingly complex, achieving disruptive innovation grows more challenging. At the same time, recent progress in Large Language Models (LLMs) has shown strong potential for scientific hypothesis formation and…
Productive software engineering teams require effective communication and balanced contributions between team members. However, teams are often ineffective at these skills, which is detrimental to project success. Project-based university…
Thanks to the widespread availability of large-scale datasets on scholarly outputs, science itself has come under the microscope with the aim of capturing a quantitative understanding of its workings. In this study, we leverage…
Achieving the UN Sustainable Development Goals (SDGs) demands adequate levels of awareness and actions to address sustainability challenges. Software systems will play an important role in moving towards these targets. Sustainability skills…
Surprisingly promising results have been achieved by deep learning (DL) systems in recent years. Many of these achievements have been reached in academic settings, or by large technology companies with highly skilled research groups and…
Current practices of quantifying performance by productivity leads serious concerns for psychological well-being of doctoral students and influence of research environment is often neglected in research evaluations. Acknowledgements in…
Being able to access software in daily life is vital for everyone, and thus accessibility is a fundamental challenge for software development. However, given the number of accessibility issues reported by many users, e.g., in app reviews,…
The world of network science is fascinating and filled with complex phenomena that we aspire to understand. One of them is the dynamics of spreading processes over complex networked structures. Building the knowledge-base in the field where…
Software development teams have to face stress caused by deadlines, staff turnover, or individual differences in commitment, expertise, and time zones. While students are typically taught the theory of software project management, their…
A growing number of empirical software engineering researchers suggest that a complementary focus on theory is required if the discipline is to mature. A first step in theory-building involves the establishment of suitable theoretical…
There have been recent calls for research on the human side of software engineering and its impact on various factors such as productivity, developer happiness and project success. An analysis of which challenges in software engineering…
The potential disconnect between research and practice in software engineering (SE) means that the uptake of research outcomes has at times been limited. In this paper we seek to identify research approaches that are rigorous in terms of…
Researchers generally place the most trust in peer-reviewed, published information, such as journals and conference papers. By contrast, software engineering (SE) practitioners typically do not have the time, access or expertise to review…
Collaboration networks provide a method for examining the highly heterogeneous structure of collaborative communities. However, we still have limited theoretical understanding of how individual heterogeneity relates to network…
Cities create potential for individuals from different backgrounds to interact with one another. It is often the case, however, that urban infrastructure obfuscates this potential, creating dense pockets of affluence and poverty throughout…
While the methodological rigor of computing research has improved considerably in the past two decades, quantitative software engineering research is hampered by immature measures and inattention to theory. Measurement-the principled…
In the domain of software engineering, our efforts as researchers to advise industry on which software practices might be applied most effectively are limited by our lack of evidence based information about the relationships between context…
Interdisciplinary research is fundamental when it comes to tackling complex problems in our highly interlinked world, and is on the rise globally. Yet, it is unclear why--in an increasingly competitive academic environment--one should…
Background. As artificial intelligence and AI-powered systems continue to grow, the role of data scientists has become essential in software development environments. Data scientists face challenges related to managing large volumes of data…