Integrating the common variability language with multilanguage annotations for web engineering

Web applications development involves managing a high diversity of files and resources like code, pages or style sheets, implemented in different languages. To deal with the automatic generation of custom-made configurations of web applications, industry usually adopts annotation-based approaches even though the majority of studies encourage the use of composition-based approaches to implement Software Product Lines. Recent work tries to combine both approaches to get the complementary benefits. However, technological companies are reticent to adopt new development paradigms such as feature-oriented programming or aspect-oriented programming. Moreover, it is extremely difficult, or even impossible, to apply these programming models to web applications, mainly because of their multilingual nature, since their development involves multiple types of source code (Java, Groovy, JavaScript), templates (HTML, Markdown, XML), style sheet files (CSS and its variants, such as SCSS), and other files (JSON, YML, shell scripts). We propose to use the Common Variability Language as a composition-based approach and integrate annotations to manage fine grained variability of a Software Product Line for web applications. In this paper, we (i) show that existing composition and annotation-based approaches, including some well-known combinations, are not appropriate to model and implement the variability of web applications; and (ii) present a combined approach that effectively integrates annotations into a composition-based approach for web applications. We implement our approach and show its applicability with an industrial real-world system.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Lightweight, semi-automatic variability extraction: a case study on scientific computing

In scientific computing, researchers often use feature-rich software frameworks to simulate physical, chemical, and biological processes. Commonly, researchers follow a clone-and-own approach: Copying the code of an existing, similar simulation and adapting it to the new simulation scenario. In this process, a user has to select suitable artifacts (e.g., classes) from the given framework and replaces the existing artifacts from the cloned simulation. This manual process incurs substantial effort and cost as scientific frameworks are complex and provide large numbers of artifacts. To support researchers in this area, we propose a lightweight API-based analysis approach, called VORM, that recommends appropriate artifacts as possible alternatives for replacing given artifacts. Such alternative artifacts can speed up performance of the simulation or make it amenable to other use cases, without modifying the overall structure of the simulation. We evaluate the practicality of VORM—especially, as it is very lightweight but possibly imprecise—by means of a case study on the DUNE numerics framework and two simulations from the realm of physical simulations. Specifically, we compare the recommendations by VORM with recommendations by a domain expert (a developer of DUNE). VORM recommended 34 out of the 37 artifacts proposed by the expert. In addition, it recommended 2 artifacts that are applicable but have been missed by the expert and 32 artifacts not recommended by the expert, which however are still applicable in the simulation scenario with slight modifications. Diving deeper into the results, we identified an undiscovered bug and an inconsistency in DUNE, which corroborates the usefulness of VORM