In a recent study, Reinforcement Learning (RL) used in combination with many-objective search, has been shown to outperform alternative techniques (random search and many-objective search) for online testing of Deep Neural Network-enabled systems. ...

Explainable artificial intelligence (XAI) is a field of study that focuses on the development process of AI-based systems while making their decision-making processes understandable and transparent for users. Research already identified ...

Modern Code Review (MCR) has become an essential practice in pull-based development since reviewers may provide insights for improvements, such as code refactoring, in Pull Requests (PRs). A recent study explored PRs in light of refactoring-...

The research area of Software Defect Prediction (SDP) is both extensive and popular, and is often treated as a classification problem. Improvements in classification, pre-processing and tuning techniques, (together with many factors which can ...

Neural Machine Translation (NMT) has experienced significant growth over the last decade. Despite these advancements, machine translation systems still face various issues. In response, metamorphic testing approaches have been introduced for ...

Programmer’s block, akin to writer’s block, is a phenomenon where capable programmers struggle to create code. Despite anecdotal evidence, no scientific studies have explored the relationship between programmer’s block and writer’s block.

Real-world software systems are often tested in multiple operating systems (OSs). Consequently, developers may need to handle specific OS requirements in tests. For example, different OSs have distinct file path name conventions (e.g.,  ...

The Python programming language features several functional constructs which can bring some benefits, e.g., fewer side effects, easier parallelization, or, in some cases, better comprehensibility due to concise code. This paper investigates the ...$\mathrm{}$

Traditionally, software development teams in many industries have used copies of production databases or their masked, anonymized, or obfuscated versions for testing. However, privacy protection regulations, for example, the General Data ...

Code review, the discussion around a code change among humans, forms a communication network that enables its participants to exchange and spread information. Although reported by qualitative studies, our understanding of the capability ...

Code Clone Detection (CCD) is a software engineering task that is used for plagiarism detection, code search, and code comprehension. Recently, deep learning-based models have achieved an F1-Score (a metric used to assess classifiers) of $\sim$...

Anxiety about giving and receiving code reviews has been documented as a common occurrence that leads to developers avoiding code reviews by procrastinating and limiting their cognitive engagement with them. This avoidance not only increases ...

An increasing demand is observed in various domains to employ Machine Learning (ML) for solving complex problems. ML models are implemented as software components and deployed in Machine Learning Software Systems (MLSSs).

There is a ...

Many studies have investigated the perception of software development teams about gender bias, inclusion policies, and the impact of remote work on productivity. The studies indicate that mothers and fathers working in the software industry ...

Empirical studies with human participants (e.g., controlled experiments) are established methods in Software Engineering (SE) research to understand developers’ activities or the pros and cons of a technique, tool, or practice. Various ...

Indentation is an old technique that emphasizes elements in source code using white spaces or tabs. But while this technique has been taught and applied for decades, evidence for its effectiveness is weak: up to 2022 relatively few experiments can ...${}_{}^{\mathrm{}}$$\frac{{}_{}}{{}_{\mathit{}}}$${}_{}^{\mathrm{}}$

Code smells (CS) are symptoms of poor design and implementation choices that may lead to increased defect incidence, decreased code comprehension, and longer times to release. Web applications and systems are seldom studied, probably due to ...

We investigated whether (possibly wrong) security patches suggested by Automated Program Repairs (APR) for real world projects are recognized by human reviewers. We also investigated whether knowing that a patch was produced by an ...

Despite the accuracy of machine learning (ML) techniques in predicting invalid bug reports, as shown in earlier research, and the importance of early identification of invalid bug reports in software maintenance, the adoption of ML techniques for ...

Building past snapshots of a software project has shown to be of interest both for researchers and practitioners. However, little attention has been devoted specifically to tests available in those past snapshots, which are fundamental for the ...