Context: Several tertiary studies have criticized the reporting of software engineering
secondary studies. Objective: Our objective is to identify guidelines for reporting software …

Software Engineering (SE) researchers are increasingly paying attention to organizational
and human factors. Rather than focusing only on variables that can be directly measured …

Highly imbalanced data typically make accurate predictions difficult. Unfortunately, software
defect datasets tend to have fewer defective modules than non-defective modules. Synthetic …

Autonomous vehicles must operate safely in their dynamic and continuously-changing
environment. However, the operating environment of an autonomous vehicle is complicated …

Software startup companies develop innovative, software-intensive products within limited
time frames and with few resources, searching for sustainable and scalable business …

Existing research mostly improves the fairness of Machine Learning (ML) software regarding
a single protected attribute at a time, but this is unrealistic given that many users have …

Software engineering is a socio-technical endeavor, and while many of our contributions
focus on technical aspects, human stakeholders such as software developers are directly …

Software development includes diverse tasks such as implementing new features, analyzing
requirements, and fixing bugs. Being an expert in those tasks requires a certain set of skills …

Machine Learning Operations (MLOps) is the practice of streamlining and optimising the
machine learning (ML) workflow, from development to deployment, using DevOps (software …

Fixing software bugs can be colossally expensive, especially if they are discovered in the
later phases of the software development life cycle. As such, bug prediction has been a …