Preprocessor-Based Variability in Open-Source and Industrial Software Systems: An Empirical Study

Overview

Almost any sufficiently complex software system today is configurable. Conditional compilation is a simple variability-implementation mechanism that is widely used in open-source projects and industry. Especially, the C~preprocessor CPP is very popular in practice, but it is also gaining (again) interest in academia. Although there have been several attempts to understand and improve CPP, there is a lack of understanding of how it is used in open-source and industrial systems and whether different usage patterns have emerged. The background is that much research on configurable systems and product lines concentrates on open-source systems, simply because of they are available for study in the first place. This leads to the potentially problematic situation that it is unclear whether the results obtained from these studies are transferable to industrial systems. We aim at lowering this gap by comparing the use of CPP in open-source projects and industry, based on a substantial set of subject systems and well-known variability metrics, including size, scattering, and tangling metrics. A key result of our empirical study is that, regarding almost all aspects we studied, open-source systems and industrial systems are similar, including systems that have been developed in industry and made open source at some point. So, there is evidence that, regarding CPP as variability-implementation mechanism, insights, methods, and tools developed based on studies of open-source systems are transferable to industrial systems.

Tools

cppstats is a tool for analyzing software systems regarding their variability. It can be used to obtain information about the usage of CPP in C software projects. The official homepage of the tool can be found under http://fosd.net/cppstats.
For the measurements in the context of our study, we extended cppstats and applied it to all of the subject systems. Our modified version is available on Github: https://github.com/clhunsen/cppstats.

Sample Systems

Analysis

Metrics

Data Visualization

Data

A table with the raw data is provided on a subpage.

The data is also available for download below.

Download

• Enhanced version of cppstats on GitHub: https://github.com/clhunsen/cppstats
• Data as CSV files as well as R and bash scripts we used: data_and_scripts.zip

Contact

• Claus Hunsen (University of Passau, Germany)
• Bo Zhang (University of Kaiserslautern, Germany)
• Janet Siegmund (University of Passau, Germany)
• Christian Kästner (Carnegie Mellon University, USA)
• Olaf Leßenich (University of Passau, Germany)
• Martin Becker (Fraunhofer Institute Experimental Software Engineering, Germany)
• Sven Apel (University of Passau, Germany)