Related papers: Cognitive Biases in Software Engineering: A System…
Sustainability is an increasingly-studied topic in software engineering in general, and in software architecture in particular. There are already a number of secondary studies addressing sustainability in software engineering, but no such…
Software engineering is not only about technical solutions. To a large extent, it is also concerned with organizational issues, project management, and human behavior. There are serious gender issues that can severely limit the…
[Background] The MVP concept has influenced the way in which development teams apply Software Engineering practices. However, the overall understanding of this influence of MVPs on SE practices is still poor. [Objective] Our goal is to…
Software is a field of rapid changes: the best technology today becomes obsolete in the near future. If we review the graduate attributes of any of the software engineering programs across the world, life-long learning is one of them. The…
Large Language Models (LLMs) are trained on large corpora written by humans and demonstrate high performance on various tasks. However, as humans are susceptible to cognitive biases, which can result in irrational judgments, LLMs can also…
When writing software code, developers typically prioritise functionality over security, either consciously or unconsciously through biases and heuristics. This is often attributed to tangible pressures such as client requirements, but…
Empirical software engineering is concerned with measuring, or estimating, both the effort put into the software process and the quality of its product. We defend the idea that measuring process effort and product quality and establishing a…
Human-AI collaboration increasingly drives decision-making across industries, from medical diagnosis to content moderation. While AI systems promise efficiency gains by providing automated suggestions for human review, these workflows can…
Context: Continuous integration (CI) is a software engineering technique that proclaims a set of frequent activities to assure the health of the software product. Researchers and practitioners mention several benefits related to CI.…
Today's software engineering (SE) complexities require a more diverse tool set going beyond technical expertise to be able to successfully tackle all challenges. Previous studies have indicated that creativity is a prime indicator for…
Context: Gamification is an emerging subject that has been applied in different areas, bringing contributions to different types of activities. Objective: This paper aims to characterize how gamification has been adopted in non-educational…
Software misconfiguration has consistently been a major reason for software failures. Over the past two decades, much work has been done to detect and diagnose software misconfigurations. However, there is still a gap between real-world…
As the primary cause of software defects, human error is the key to understanding, and perhaps to predicting and avoiding them. Little research has been done to predict defects on the basis of the cognitive errors that cause them. This…
Machine learning's widespread adoption in decision-making processes raises concerns about fairness, particularly regarding the treatment of sensitive features and potential discrimination against minorities. The software engineering…
While recent years have witnessed a rapid growth of research papers on recommender system (RS), most of the papers focus on inventing machine learning models to better fit user behavior data. However, user behavior data is observational…
Large language models (LLMs) offer significant potential as tools to support an expanding range of decision-making tasks. Given their training on human (created) data, LLMs have been shown to inherit societal biases against protected…
Behavioral science has witnessed an explosion in the number of biases identified by behavioral scientists, to more than 200 at present. This article identifies the 10 most important behavioral biases for project management. First, we argue…
Context: Empirical Software Engineering (ESE) drives innovation in SE through qualitative and quantitative studies. However, concerns about the correct application of empirical methodologies have existed since the 2006 Dagstuhl seminar on…
The design of effective programming languages, libraries, frameworks, tools, and platforms for data engineering strongly depends on their ease and correctness of use. Anyone who ignores that it is humans who use these tools risks building…
Machine learning models are increasingly being used in important decision-making software such as approving bank loans, recommending criminal sentencing, hiring employees, and so on. It is important to ensure the fairness of these models so…