Code Smells & Software Quality in Machine Learning Projects

Artificial Intelligence (AI) and Machine Learning (ML) are pervasive in the current computer science landscape. Yet, there still exists a lack of Software Engineering (SE) experience and best practices in this field. One such best practice, static code analysis, can be used to find code smells, i.e., (potential) defects in the source code,...

Enabling domain experts to participate in the process of improving software quality using change impact analysis

Software engineers often lack the domain knowledge needed to validate context specific parts of software. Domain experts do have this knowledge needed to validate the software, but often lack the expertise and tools to apply this knowledge in a way that tests the software product. Based on a case study at business-software company Exact, this...

Releasing Fast and Slow: Characterizing Rapid Releases in a Large Software-Driven Organization

The appeal of delivering new features faster has led many software projects to change their development processes towards rapid release models. Even though rapid releases are increasingly being adopted in open-source and commercial software, it is not well understood what the effects are of this practice. This thesis presents an exploratory case...

Investigation of the impact of cohesion on the change-proneness of Java interfaces

A lack of cohesion is often associated with bad software quality, and could lead to more changes and bugs in software. In this thesis the impact of cohesion on the change-proneness of Java interfaces is investigated. Showing the existence of a relation between these concepts can lead to better change prediction models that can support software...