The behavior of software that uses the Java Reflection API is fundamentally hard to predict
by analyzing code. Only recent static analysis approaches can resolve reflection under …

Data preprocessing remains an important step in machine learning studies. This is because
proper preprocessing of imbalanced data can enable researchers to reduce defects as …

A great part of software development involves conceptualizing or communicating the
underlying procedures and logic that needs to be expressed in programs. One major …

Over the past decade with the rise of the Mining Software Repositories (MSR) field, the
modelling of defects for large and long-lived systems has become one of the most common …

Code quality metrics are widely used to identify design flaws (eg, code smells) as well as to
act as fitness functions for refactoring recommenders. Both these applications imply a strong …

Assessing the exploitability of software vulnerabilities at the time of disclosure is difficult and
error-prone, as features extracted via technical analysis by existing metrics are poor …

Static analysis tools have showcased their importance and usefulness in automated
detection of code anomalies and defects. However, the large number of alarms reported and …

Static analysis tools have showcased their importance and usefulness in automated
detection of defects. However, the tools are known to generate a large number of alarms …

Background: The Java programming language version eighth introduced a number of
features that encourage the functional style of programming, including the support for …

Many statistical analyses and prediction models rely on past data about how a system
evolves to learn and anticipate the number of changes and bugs it will have in the future. As …