A Code Tagging Approach to Software Product Line Development:An Application to Satellite Communication Libraries

International audienceSoftware product line engineering seeks to systematise reuse when developing families of similar software systems so as to minimise development time, cost and defects. To realise variability at the code level, product line methods classically advocate usage of inheritance, components, frameworks, aspects or generative techniques. However, these might require unaffordable paradigm shifts for developers if the software was not thought at the outset as a product line. Furthermore, these techniques can be conflicting with a company's coding practices or external regulations. These concerns were the motivation for the industry- university collaboration described in this paper in which we developed a minimally intrusive coding technique based on tags. The approach was complemented with traceability from code to feature diagrams which were exploited for automated configuration. It is supported by a toolchain and is now in use in the partner company for the development of flight grade satellite communica- tion software libraries

Variability Bugs in Highly Configurable Systems: A Qualitative Analysis

Variability-sensitive verification pursues effective analysis of the exponentially many variants of a program family. Several variability-aware techniques have been proposed, but researchers still lack examples of concrete bugs induced by variability, occurring in real large-scale systems. A collection of real world bugs is needed to evaluate tool implementations of variability-sensitive analyses by testing them on real bugs. We present a qualitative study of 98 diverse variability bugs (i.e., bugs that occur in some variants and not in others) collected from bug-fixing commits in the Linux, Apache, BusyBox, and Marlin repositories. We analyze each of the bugs, and record the results in a database. For each bug, we create a self-contained simplified version and a simplified patch, in order to help researchers who are not experts on these subject studies to understand them, so that they can use these bugs for evaluation of their tools. In addition, we provide single-function versions of the bugs, which are useful for evaluating intra-procedural analyses. A web-based user interface for the database allows to conveniently browse and visualize the collection of bugs. Our study provides insights into the nature and occurrence of variability bugs in four highly-configurable systems implemented in C/C++, and shows in what ways variability hinders comprehension and the uncovering of software bugs.</jats:p

Yo Variability! JHipster: A Playground for Web-Apps Analyses

International audienceThough variability is everywhere, there has always been a shortage of publicly available cases for assessing variability-aware tools and techniques as well as supports for teaching variability-related concepts. Historical software product lines contains industrial secrets their owners do not want to disclose to a wide audience. The open source community contributed to large-scale cases such as Eclipse, Linux kernels, or web-based plugin systems (Drupal, WordPress). To assess accuracy of sampling and prediction approaches (bugs, performance), a case where all products can be enumerated is desirable. As configuration issues do not lie within only one place but are scattered across technologies and assets, a case exposing such diversity is an additional asset. To this end, we present in this paper our efforts in building an explicit product line on top of JHipster, an industrial open-source Web-app configurator that is both manageable in terms of configurations (~ 163,000) and diverse in terms of technologies used. We present our efforts in building a variability-aware chain on top of JHipster's configurator and lessons learned using it as a teaching case at the University of Rennes. We also sketch the diversity of analyses that can be performed with our infrastructure as well as early issues found using it. Our long term goal is both to support students and researchers studying variability analysis and JHipster developers in the maintenance and evolution of their tools