In 2006, Fowler and Foemmel defined ten core Continuous Integration (CI) practices that
could increase the speed of software development feedback cycles and improve software …

Developing machine learning algorithms for time-series data often requires manual
annotation of the data. To do so, graphical user interfaces (GUIs) are an important …

Evaluating and predicting software maintenance effort using source code metrics is one of
the holy grails of software engineering. Unfortunately, previous research has provided …

Code metrics have been widely used to estimate software maintenance effort. Metrics have
generally been used to guide developer effort to reduce or avoid future maintenance …

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 …

The cost of software maintenance often surpasses the initial development expenses, making
it a significant concern for the software industry. A key strategy for alleviating future …

Self-Admitted Technical Debt (SATD) refers to the phenomenon where developers explicitly
acknowledge technical debt through comments in the source code. While considerable …

In this folklore-confirmation short paper, we present the results of a study on the removal of
dead code. We aim to gather evidence on the impact of dead-method removal on the …

Technical debt in software development is a common problem that is overlooked by many
development teams. This debt can be generated from a variety of reasons, including time …

Software metrics are often used to reflect vulnerabilities in program code to measure the
complexity of each software module. Knowing the complexity of each software module is an …