Fifth international workshop on languages for modelling variability (MODEVAR@SPLC 2022)

Fifth International Workshop on Languages for Modelling Variability (MODEVAR@SPLC 2022) Jose-Miguel Horcas University of Sevilla Sevilla, Spain [email protected] Angela Villota Universidad Icesi Cali, Colombia [email protected] David Benavides University of Sevilla Sevilla, Spain [email protected] Philippe Collet Université Côte d’Azur, CNRS, I3S Sophia Antipolis, France [email protected] ABSTRACT Feature models were invented in 1990 and have been recognised as one of the main contributions to the Software Product Line community. Although there have been several attempts to establish and study a sort of standard variability modelling language, there is still no consensus on a simple feature modelling language. There can be many motivations to have one but among others, there is one that is very important: information sharing among researchers, tools and developers. Following the spirit of the four previous editions, this workshop is an interactive event where all participants share knowledge, but also ongoing realizations about how to build up a feature modelling language that all the community can agree on. CCS CONCEPTS •Software and its engineering →Software product lines. KEYWORDS feature models, variability modelling languages and tools ACM Reference Format: Jose-Miguel Horcas, Angela Villota, David Benavides, and Philippe Collet. 2022. Fifth International Workshop on Languages for Modelling Variability (MODEVAR@SPLC 2022). In 26th ACM International Systems and Software Product Line Conference - Volume A (SPLC ’22), September 12–16, 2022, Graz, Austria. ACM, New York, NY, USA, 1 page. https://doi.org/10.1145/3546932. 3547075 1 MODEVAR WORKSHOP The main topic of discussion of this workshop is variability modelling languages, concepts, usages and tools. In 1990 [ 4 ], feature models were proposed as a way of modelling variability. Since then, this contribution is among the most important ones in the software product line history. Nevertheless, there have been many feature modelling dialects [ 5 ] while more languages and environments with different functionalities were also developed [ 1 ]. In parallel, CVL [ 3 ] aimed at being a standard and common variability language, but the standardisation process failed. Recently, a family of industrial standards such as ISO/IEC 26558:2017 were released. As a Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). SPLC ’22, September 12–16, 2022, Graz, Austria https://doi.org/10.1145/3546932.3547075 community, we are missing a simple common variability modelling language for academic purposes as a first output. From there, we expect to advance the state of the art for those that model and manage variability in some form. We cannot share easily our models and we cannot have a sort of universal feature model repository where we could post our outputs using a common notation. Other communities do have such kind of languages such as CNF for SAT solving or XCSP for constraint programming, to mention a few. In this context, this workshop (https://modevar.github.io/) intends to continue the effort started by its four first editions: join forces to make what could be an important contribution to the community. It aims to reach a consensus on the main modelling constructs and the language’s syntax, so to have a big enough and representative consortium that supports the proposal and builds together a reference implementation. This year keeps the focus of the previous edition, with new ideas about the common language and advances on solutions regarding its possible implementations. The workshop first expects the presentation of new insights on industrial and academic needs to complement the usage scenarios devised in the first edition [ 2 ]. Proposals and updates on some of the language levels [ 6 ] previously determined, on the possible support for interoperability and storage of variability models are also expected. After the presentations, discussions are structured in small focused working groups to make advances over the language, its implementation, and the next steps to prepare dissemination. ACKNOWLEDGMENTS This work was supported by the project OPHELIA (RTI2018-101204-B-C22) funded by FEDER/Ministry of Science and Innovation — State Research Agency; the COPERNICA (P20_01224) and METAMORFOSIS (FEDER_US-1381375) projects funded by Junta de Andalucía; and Juan de la Cierva—Formación 2019 grant. REFERENCES [1] Rabih Bashroush, Muhammad Garba, Rick Rabiser, Iris Groher, and Goetz Botterweck. 2017. Case tool support for variability management in software product lines. ACM Computing Surveys (CSUR) 50, 1 (2017), 14. [2] Thorsten Berger and Philippe Collet. 2019. Usage scenarios for a common feature modeling language. In 23rd International Systems and Software Product Line Conference (SPLC), Vol. B. ACM, 86:1–86:8. https://doi.org/10.1145/3307630.3342403 [3] Øystein Haugen, Andrzej Wąsowski, and Krzysztof Czarnecki. 2013. CVL: common variability language. In 17th Int’l Software Product Line Conf. ACM, 277–277. [4] Kyo C Kang, Sholom G Cohen, James A Hess, William E Novak, and A Spencer Peterson. 1990. Feature-oriented domain analysis (FODA) feasibility study. Technical Report. SEI, Carnegie-Mellon Univ. [5] Pierre-Yves Schobbens, Patrick Heymans, Jean-Christophe Trigaux, and Yves Bontemps. 2007. Generic semantics of feature diagrams. Computer Networks 51, 2 (2007), 456–479. [6] Thomas Thüm, Christoph Seidl, and Ina Schaefer. 2019. On language levels for feature modeling notations. In 23rd SPLC, Vol. B. ACM, 83:1–83:4. https: //doi.org/10.1145/3307630.3342404