Customizable Visualization of Quality Metrics for Object-Oriented Variability Implementations

Description

Many large-scale software systems intensively implement variability to reuse software and speed up development. Such mechanisms, however, bring additional complexity, which eventually leads to technical debt, threatening the software quality, and hampering maintenance and evolution. This is especially the case for variability-rich object-oriented (OO) systems that implement variability in a single codebase. They heavily rely on existing OO mechanisms to implement their variability, making them especially prone to variability debt at the code level. In this paper, we propose VariMetrics, an extension of a visualization relying on the city metaphor to reveal such zones of indebted OO variability implementations. VariMetrics extends the VariCity visualization and displays standard OO quality metrics, such as code duplication, code complexity, or test coverage, as additional visual properties on the buildings representing classes. Extended configuration options allow the user to choose and combine quality metrics, uncovering the critical zones of OO variability implementations. We evaluate VariMetrics both by reporting on the exposed quality-critical zones found on multiple large open-source projects, and by correcting the reported issues in such zones of one project, showing an improvement in quality.

Abstract

Pre-print to be published in the 26th ACM International Systems and Software Product Line Conference - Volume A (SPLC '22), September 12–16, 2022, Graz, Austria.

Abstract

International audience

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