Software Vulnerability Prediction (SVP) is a data-driven technique for software quality
assurance that has recently gained considerable attention in the Software Engineering …

Software fault prediction (SFP) aims to improve software quality with a possible minimum
cost and time. Various machine learning models have been proposed in the past for …

The use of learning-based techniques to achieve automated software vulnerability detection
has been of longstanding interest within the software security domain. These data-driven …

Today, data availability has gone from scarce to superabundant. Technologies like IoT,
trends in social media and the capabilities of smart-phones are producing and digitizing lots …

This book is an introduction to social data analytics along with its challenges and
opportunities in the age of Big Data and Artificial Intelligence. It focuses primarily on …

Context Publicly available software cost estimation datasets are outdated and may not
represent current industrial environments. Thus most research has concentrated on the …

Data is a cornerstone of empirical software engineering (ESE) research and practice. Data
underpin numerous process and project management activities, including the estimation of …

The amount of data for machine learning (ML) applications is constantly growing. Not only
the number of observations, especially the number of measured variables (features) …

Abstract Machine Learning (ML) is integrated into a growing number of systems for various
applications. Because the performance of an ML model is highly dependent on the quality of …

For organizations data quality is a prerequisite for automated decision making and agility. To
provide high quality data, numerous tools have emerged that support the different steps of …