Machine learning (ML) techniques increase the effectiveness of software engineering (SE)
lifecycle activities. We systematically collected, quality-assessed, summarized, and …

Internet of Things (IoT) is an emerging technology that has the promising power to change
our future. Due to the market pressure, IoT systems may be released without sufficient …

Despite excellent average-case performance of many image classifiers, their performance
can substantially deteriorate on semantically coherent subgroups of the data that were …

Random testing (RT) is a well-studied testing method that has been widely applied to the
testing of many applications, including embedded software systems, SQL database systems …

The analysis of software product lines is challenging due to the potentially large number of
products, which grow exponentially in terms of the number of features. Product sampling is a …

Quality assurance for product lines is often infeasible for each product separately. Instead,
only a subset of all products (ie, a sample) is considered during testing such that at least the …

Product lines are ubiquitous for managing variable systems. The variability of a product line
is typically described in terms of a feature model. Analyzing a feature model gives insight …

Software module clustering is an unsupervised learning method used to cluster software
entities (eg, classes, modules, or files) with similar features. The obtained clusters may be …

Deep learning-based approaches have gained popularity for environment perception tasks
such as semantic segmentation and object detection from images. However, the different …

Code analysis brings excellent benefits to software development, maintenance, and quality
assurance. Various tools can uncover code defects or even software bugs in a range of …