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We address the problem of automating 1) the analysis of existing similar model variants and 2) migrating them into a software product line. Our approach, named MoVa2PL, considers the identification of variability and commonality in model variants, as well as the extraction of a CVL-compliant Model-based Software Product Line (MSPL) from the features identified on these variants. MoVa2PL builds on a generic representation of models making it suitable to any MOF-based models. We apply our approach on variants of the open source ArgoUML UML modeling tool as well as on variants of an Inflight Entertainment System. Evaluation with these large and complex case studies contributed to show how our feature identification with structural constraints discovery and the MSPL generation process are implemented to make the approach valid (i.e., the extracted software product line can be used to regenerate all variants considered) and sound (i.e., derived variants which did not exist are at least structurally valid).

Abstract-Adopting Software Product Line (SPL) engineering principles demands a high up-front investment. Bottom-Up Technologies for Reuse (BUT4Reuse) is a generic and extensible tool aimed to leverage existing similar software products in order to help in extractive SPL adoption. The envisioned users are 1) SPL adopters and 2) Integrators of techniques and algorithms to provide automation in SPL adoption activities. We present the methodology it implies for both types of users and we present the validation studies that were already conducted. BUT4Reuse tool and source code are publicly available under the EPL license.

Feature location is a traceability recovery activity to identify the implementation elements associated to a characteristic of a system. Besides its relevance for software maintenance of a single system, feature location in a collection of systems received a lot of attention as a first step to re-engineer system variants (created through clone-and-own) into a Software Product Line (SPL). In this context, the objective is to unambiguously identify the boundaries of a feature inside a family of systems to later create reusable assets from these implementation elements. Among all the case studies in the SPL literature, variants derived from ArgoUML SPL stands out as the most used one. However, the use of different settings, or the omission of relevant information (e.g., the exact configurations of the variants or the way the metrics are calculated), makes it difficult to reproduce or benchmark the different feature location techniques even if the same ArgoUML SPL is used. With the objective to foster the research area on feature location, we provide a set of common scenarios using ArgoUML SPL and a set of utils to obtain metrics based on the results of existing and novel feature location techniques.

Handling large-scale software variability is still a challenge for many organizations. After decades of research on variability management concepts, many industrial organizations have introduced techniques known from research, but still lament that pure textbook approaches are not applicable or efficient. For instance, software product line engineering-an approach to systematically develop portfolios of products-is difficult to adopt given the high upfront investments; and even when adopted, organizations are challenged by evolving their complex product lines. Consequently, the research community now mainly focuses on reengineering and evolution techniques for product lines; yet, understanding the current state of adoption and the industrial challenges for organizations is necessary to conceive effective techniques. In this multiple-case study, we analyze the current adoption of variability management techniques in twelve medium-to large-scale industrial cases in domains such as automotive, aerospace or railway systems. We identify the current state of variability management, emphasizing the techniques and concepts they adopted. We elicit the needs and challenges expressed for these cases, triangulated with results from a literature review. We believe our results help to understand the current state of adoption and shed light on gaps to address in industrial practice.

International audience—Software Product Line Engineering is a mature approach enabling the derivation of product variants by assem-bling reusable assets. In this context, domain experts widely use Feature Models as the most accepted formalism for capturing commonality and variability in terms of features. Feature Models also describe the constraints in feature combinations. In industrial settings, domain experts often deal with Software Product Lines with high numbers of features and constraints. Furthermore, the set of features are often regrouped in different subsets that are overseen by different stakeholders in the process. Consequently, the management of the complexity of large Feature Models becomes challenging. In this paper we propose a dedicated interactive visualisation paradigm to help domain experts and stakeholders to manage the challenges in maintaining the con-straints among features. We build Feature Relations Graphs (FRoGs) by mining existing product configurations. For each feature, we are able to display a FRoG which shows the impact, in terms of constraints, of the considered feature on all the other features. The objective is to help domain experts to 1) obtain a better understanding of feature constraints, 2) potentially refine the existing feature model by uncovering and formalizing missing constraints and 3) serve as a recommendation system, during the configuration of a new product, based on the tendencies found in existing configurations. The paper illustrates the visualisation paradigm with the industrial case study of Renault's Electric Parking System Software Product Line

Reengineering a Software Product Line from legacy variants remains a challenging endeavour. Among various challenges, it is a complex task to retrieve enough information for inferring the variability from experts' domain knowledge and from the semantics of software elements. We propose the VariClouds process that can be leveraged by domain experts to understand the semantics behind the different blocks identified during software variants analysis. VariClouds is based on interactive word cloud visualisations providing name suggestions for these blocks using tf-idf as weighting factor. We evaluate our approach by assessing its added-value to several previous works in the literature where no tool support was provided to domain experts to characterise features from software blocks. CCS Concepts •Software and its engineering → Software reverse engineering; Software product lines;

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