The Symposium on Search-Based Software Engineering: Past, Present and Future

CONTEXT: Search-Based Software Engineering (SBSE) is the research field where Software Engineering (SE) problems are modelled as search problems to be solved by search-based techniques. The Symposium on Search Based Software Engineering (SSBSE) is the premier event on SBSE, which had its 11th edition in 2019. OBJECTIVE: In order to better understand the characteristics and evolution of papers published at SSBSE, this work reports results from a mapping study targeting the proceedings of all SSBSE editions. Despite the existing mapping studies on SBSE, our contribution in this work is to provide information to researchers and practitioners willing to enter the SBSE field, being a source of information to strengthen the symposium, guide new studies, and motivate new collaboration among research groups. METHOD: A systematic mapping study was conducted with a set of four research questions, in which 134 studies published in all editions of SSBSE, dated from 2009 to 2019, were evaluated. In a fifth question, 32 papers published in the challenge track were summarised. RESULTS: Throughout the years, 290 authors from 25 countries have contributed to the main track of the symposium, with the collaboration of at least two institutions in 46.3% of the papers. SSBSE papers have got substantial external visibility, as most citations are from different venues. The SE tasks addressed by SSBSE are mostly related to software testing, software debugging, software design, and maintenance. Evolutionary algorithms are present in 75% of the papers, being the most common search technique. The evaluation of the SBSE approaches usually includes industrial systems. CONCLUSIONS: SSBSE has helped increase the popularity of SBSE in the SE research community and has played an important role on making SBSE mature. There are still problems and challenges to be addressed in the SBSE field, which can be tackled by SSBSE authors in further studies

Merging cloned alloy models with colorful refactorings

Likewise to code, clone-and-own is a common way to create variants of a model, to explore the impact of different features while exploring the design of a software system. Previously, we have introduced Colorful Alloy, an extension of the popular Alloy language and toolkit to support feature-oriented design, where model elements can be annotated with feature expressions and further highlighted with different colors to ease understanding. In this paper we propose a catalog of refactorings for Colorful Alloy models, and show how they can be used to iteratively merge cloned Alloy models into a single feature-annotated colorful model, where the commonalities and differences between the different clones are easily perceived, and more efficient aggregated analyses can be performed.This work is financed by the ERDF — European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation – COMPETE 2020 Programme and by National Funds through the Portuguese funding agency, FCT – Fundação para a Ciência e a Tecnologia within project PTDC/CCI-INF/29583/2017 – POCI-01-0145-FEDER-029583

Guiding Clone-and-Own When Creating Unplanned Products from a Software Product Line

International audienceClone-and-own is a simple and intuitive practice adopted to construct new product variants based on existing ones. However, when the developed family of products becomes rich, maintaining shared assets and managing variability between the clones become tedious tasks. Therefore, migrating the family of products into a software product line becomes essential. Despite that, software engineers remain interested in constructing new product variants that are not provided by the software product line. In this short paper, we briefly present our approach to guide software engineers in deriving new products from a software product line based on clone-and-own. This approach consists of proposing the possible configuration scenarios by means of operations to perform at asset level, in order to derive a new product variant