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Context: Advancements in machine learning (ML) lead to a shift from the traditional view of software development, where algorithms are hard-coded by humans, to ML systems materialized through learning from data. Therefore, we need to…
Higher education provides a solid theoretical and practical, but mostly technical, background for the aspiring software developer. Research, however, has shown that graduates still fall short of the expectations of industry. These…
Large Language Models (LLMs) have significantly impacted numerous domains, including Software Engineering (SE). Many recent publications have explored LLMs applied to various SE tasks. Nevertheless, a comprehensive understanding of the…
In the short period since the release of ChatGPT, large language models (LLMs) have changed the software engineering research landscape. While there are numerous opportunities to use LLMs for supporting research or software engineering…
Systematic Literature Reviews (SLRs) are a widely employed research method in software engineering. However, there are several problems with SLRs, including the enormous time and effort to conduct them and the lack of obvious impacts of SLR…
Computer science (CS) education needs to evolve to support software and artificial intelligence (AI) systems engineering, and it needs to happen now -- precisely because the core intellectual contributions of CS have never been more…
Machine learning (ML) techniques increase the effectiveness of software engineering (SE) lifecycle activities. We systematically collected, quality-assessed, summarized, and categorized 83 reviews in ML for SE published between 2009-2022,…
Software is a key component of solutions for 21st Century problems. These problems are often "wicked", complex, and unpredictable. To provide the best possible solution, millennial software engineers must be prepared to make ethical…
Following the rise of large language models (LLMs), many studies have emerged in recent years focusing on exploring the adoption of LLM-based tools for software development by novice developers: computer science/software engineering…
Existing work on the practical impact of software engineering (SE) research examines industrial relevance rather than adoption of study results, hence the question of how results have been practically applied remains open. To answer this…
Sustainability is increasingly recognized as a critical dimension of engineering education, yet its integration into Software Engineering curricula remains a challenge. This paper reports on a case study that examines how sustainability is…
This paper provides a survey of the emerging area of Large Language Models (LLMs) for Software Engineering (SE). It also sets out open research challenges for the application of LLMs to technical problems faced by software engineers. LLMs'…
Although tension between university curricula and industry expectations has existed in some form for decades, the rapid integration of generative AI (GenAI) tools into software development has recently widened the gap between the two…
Background: The software engineering community has increasingly conducted systematic literature reviews (SLR) as a means to summarize evidence from different studies and bring to light the state of the art of a given research topic. While…
The discipline of software engineering (SE) combines social and technological dimensions. It is an interdisciplinary research field. However, interdisciplinary research submitted to software engineering venues may not receive the same level…
Context: Systematic Literature Reviews (SLRs) have been adopted within Software Engineering (SE) for more than a decade to provide meaningful summaries of evidence on several topics. Many of these SLRs are now potentially not fully…
Software engineering (SE) research should be relevant to industrial practice. There have been regular discussions in the SE community on this issue since the 1980's, led by pioneers such as Robert Glass. As we recently passed the milestone…
Context: Empirical Software Engineering (ESE) faces increasing challenges due to data scale, methodological complexity, and reproducibility concerns. Large Language Models (LLMs) have emerged as promising tools to support empirical…
The Information Systems (IS) and Software Engineering (SE) fields share a remarkable number of similarities in their historical evolution to date. These similarities are briefly outlined below. An analysis of 10 years (2001-2010) of…
Creativity is a critical skill that professional software engineers leverage to tackle difficult problems. In higher education, multiple efforts have been made to spark creative skills of engineering students. However, creativity is a vague…