First international workshop on languages for modelling variability (MODEVAR 2019)

First International Workshop on Languages for Modelling Variability (MODEVAR 2019) David Benavides University of Sevilla Sevilla, Spain [email protected] Rick Rabiser Johannes Kepler University Linz Linz, Austria [email protected] Don Batory University of Texas at Austin Austin, USA [email protected] Mathieu Acher Univ Rennes, Inria, CNRS, IRISA Rennes, 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 a sort of standard variability modelling language, there is still no consensus. There can be many motivations to have one but there is one that is very important: information sharing among researchers, tools or developers. This first international workshop is an interactive event where all participants shall share knowledge about how to build up a simple variability modelling language that all the community can agree on. CCS CONCEPTS •Software and its engineering →Software product lines. KEYWORDS Software product lines, variability modelling, languages ACM Reference Format: David Benavides, Rick Rabiser, Don Batory, and Mathieu Acher. 2019. First International Workshop on Languages for Modelling Variability (MODEVAR 2019). In 23rd International Systems and Software Product Line Conference - Volume A (SPLC ’19), September 9–13, 2019, Paris, France. ACM, New York, NY, USA, 1 page. https://doi.org/10.1145/3336294.3342364 MODEVAR WORKSHOP The main topic of discussion of this workshop is variability modelling languages, concepts, usages and tools. In 1990 [ 5 ], 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 that were well surveyed by some authors. Czarnecki et al. [ 2 ] provide a good historical perspective. Also, diverse other approaches not focusing on features as unit of variability exist, e.g., decision modelling [ 8 ], OVM [ 6 ], and UML-based 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 ’19, September 9–13, 2019, Paris, France https://doi.org/10.1145/3336294.3342364 variability modelling [ 3 ], to name the probably most prominent. Diverse (systematic) studies have surveyed existing variability modelling languages and approaches. Raatikainen et al. [ 7 ] published a tertiary study demonstrating the plethora of existing approaches. Bashroush et al. [ 1 ] present a survey of 37 tools for variability management/modelling. However, no standard emerged. We cannot share easily our models and we cannot have a sort of universal variability model repository where we could post our outputs using a common notation. Other communities do have such kind of languages such as DIMACS for SAT solving or XCSP for constraint programming to only mention a few. CVL [ 4 ] was proposed as a try to have a standard and common variability language with many different purposes. The project unfortunately did not end up very well. Recently, a family of industrial standards were released such as ISO/IEC 26558:2017. As a 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 not only in modelling variability but also in today’s variability managers. In this context, this workshop intends to 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 and have a big enough and representative consortium that supports the proposal. 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] Krzysztof Czarnecki, Paul Grünbacher, Rick Rabiser, Klaus Schmid, and Andrzej Wąsowski. 2012. Cool features and tough decisions: a comparison of variability modeling approaches. In 6th Int’l WS on Variability Modelling of Software-Intensive Systems. ACM, 173–182. [3] Hassan Gomaa. 2005. Designing Software Product Lines with UML. Addison-Wesley. [4] Øystein Haugen, Andrzej Wąsowski, and Krzysztof Czarnecki. 2013. CVL: common variability language. In 17th Int’l Software Product Line Conf. ACM, 277–277. [5] 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. [6] Klaus Pohl, Günter Böckle, and Frank J van Der Linden. 2005. Software Product Line Engineering: Foundations, Principles, and Techniques. Springer. [7] Mikko Raatikainen, Juha Tiihonen, and Tomi Männistö. 2019. Software product lines and variability modeling: A tertiary study. Journal of Systems and Software 149 (2019), 485–510. [8] Klaus Schmid, Rick Rabiser, and Paul Grünbacher. 2011. A comparison of decision modeling approaches in product lines. In 5th Int’l WS on Variability Modelling of Software-Intensive Systems. ACM, 119–126.