Context: Several secondary studies have investigated the relationship between internal
quality attributes, source code metrics and external quality attributes. Sometimes they have …

In recent years, Jupyter notebooks have grown in popularity in several domains of software
engineering, such as data science, machine learning, and computer science education …

Coupling and Cohesion are two fundamental concepts that can be applied to design better
modular object-oriented software. This study aims at reviewing existing research on …

Context: Nowadays, fault-proneness prediction is an important field of software engineering.
It can be used by developers and testers to prioritize tests. This would allow a better …

The difficulty of software development tasks depends on several factors including the
characteristics of the underlying source-code. These characteristics can be captured and …

In the field of Software Fault Prediction (SFP), researchers exploit software metrics to build
predictive models using machine learning and/or statistical techniques. SFP has existed for …

Many fault-proneness prediction models have been proposed in literature to identify fault-
prone code in software systems. Most of the approaches use fault data history and …

Most code-based quality measurement approaches are based, at least partially, on values of
multiple source code metrics. A class will often be classified as being of poor quality if the …

In software engineering fault proneness prediction is one of the important fields for quality
measurement using multiple code metrics. The metrics thresholds are very practical in …

Many code metrics exist for bug prediction. However, these metrics are based on the trivial
count of code properties and are not sufficient. This research article proposes three new …