Context: Automated software defect prediction (SDP) methods are increasingly applied,
often with the use of machine learning (ML) techniques. Yet, the existing ML-based …

Data are everywhere. Examples include sports data. Embedded in these data is implicit,
previously unknown and potentially useful information or knowledge to be discovered. In this …

Fake news is an ever-growing concern in the modern age of the internet. Discerning fake
information from the truthful is an important task given the simplicity of sharing information …

Software defect prediction is the process of identifying defective files and modules that need
rigorous testing. In the literature, several secondary studies including systematic reviews …

Abstract The existing Isolation Forest algorithm detects anomalies by using binary trees.
However, a few limitations can be observed. To resolve this problem, we present a …

Pipeline incidents occur throughout the world and can have devastating financial and
ecological impacts. A large amount of data is collected and made publicly available for each …

Declarative programming languages such as SwiftUI have gained increasing relevance for
user interface implementation in mobile applications. A tool for evaluating and improving the …

Software defect prediction (SDP) models often neglect the issue of multicollinearity in
training sets, particularly among software complexity metrics, which can threaten internal …

Software quality is the capability of a software process to produce software product satisfying
the end user. The quality of process or product entities is described through a set of …

I am extremely grateful for the completion of my master's thesis at TU Delft and I would like to
take this opportunity to express appreciation for all those who have supported and guided …