Benchmarking on the Automated Analyses of Feature Models: a Preliminary Roadmap

The automated analysis of Feature Models (FMs) is becoming a well-established discipline. New analysis operations, tools and techniques are rapidly proliferating in this context. However, the lack of standard mechanisms to evaluate and compare the performance of different solutions is starting to hinder the progress of this community. To address this situation, we propose the creation of a benchmark for the automated analyses of FMs. This benchmark would enable the objective and repeatable comparison of tools and techniques as well as promoting collaboration among the members of the discipline. Creating a benchmark requires a community to share a common view of the problem faced and come to agreement about a number of issues related to the design, distribution and usage of the benchmark. in this paper, we take a first step toward that direction. in particular, we first describe the main issues to be addressed for the successful development and maintenance of the benchmark. Then, we propose a preliminary research agenda setting milestones and clarifying the types of contributions expected from the community

Automated analysis of feature models 20 years later: a literature review

Software product line engineering is about producing a set of related products that share more commonalities than variabilities. Feature models are widely used for variability and commonality management in software product lines. Feature models are information models where a set of products are represented as a set of features in a single model. The automated analysis of feature models deals with the computer–aided extraction of information from feature models. The literature on this topic has contributed with a set of operations, techniques, tools and empirical results which have not been surveyed until now. This paper provides a comprehensive literature review on the automated analysis of feature models 20 years after of their invention. This paper contributes by bringing together previously-disparate streams of work to help shed light on this thriving area. We also present a conceptual framework to understand the different proposals as well as categorise future contributions. We finally discuss the different studies and propose some challenges to be faced in the future.CICYT TIN2009-07366CICYT TIN2006-00472Junta de Andalucía TIC-253

Research Article Using a Rule-based Method for Detecting Anomalies in Software Product Line

Abstract: This study proposes a rule based method for detecting anomalies in SPL. By anomalies we mean falseoptional features and wrong cardinality. Software Product Line (SPL) is an emerging methodology for software products development. Successful software product is highly dependent on the validity of a SPL. Therefore, validation is a significant process within SPL. Anomalies are well known problems in SPL. Anomiles in SPL means dead feature, redundancy, wrong-cardinality and false-option features. In the literature, the problem of false-option features and wrong cardinality did not take the signs of attentions as a dead feature and redundancy problems. The maturity of the SPL can be enhanced by detecting and removing the false-option features. Wrong cardinality can cause problems in developing software application by preventing configuration of variants from their variation points. The contributions of this study are First Order Logic (FOL) rules for deducing false-option features and wrong-cardinality. Moreover, we provide a new classification of the wrong cardinality. As a result, all cases of falseoption features and wrong variability in the domain-engineering process are defined. Finally, experiments are conducted to prove the scalability of the proposed method

Automated Analysis of Diverse Variability Models with Tool Support

Over the past twenty years, there have been many contributions in the area of automated analysis of variability models. However, the majority of these researches are focused on feature models. We propose that the knowledge obtained during recent years on the analysis of feature models can be applied to automatically analyse different variability models. In this paper we present FaMa OVM and FaMa DEB, which are prototypical implementations for the automated analysis of two distinct variability models, namely Orthogonal Variability Models and Debian Variablity Models, respectively. In order to minimise efforts and benefit from the feature model know–how, we use FaMa Framework which allows the development of analysis tools for diverse variability modelling languages. This framework provides a well tested system that guides the tool development. Due to the structure provided by the framework, FaMa OVM and FaMa DEB tools are easy to extend and integrate with other tools. We report on the main points of both tools, such as the analysis operations provided and the logical solvers used for the analysis.Comisión Interministerial de Ciencia y Tecnología (CICYT) TIN2012-32273Junta de Andalucía TIC-5906Junta de Andalucía P12-TIC-186

Defects in Product Line Models and How to Identify Them

This chapter is about generic (language-independent) verification criteria of product line models, its identification, formalisation, categorization, implementation with constraint programming techniques and its evaluation on several industrial and academic product line models represented with several languages

Automated analysis of feature models: Quo vadis?

Feature models have been used since the 90's to describe software product lines as a way of reusing common parts in a family of software systems. In 2010, a systematic literature review was published summarizing the advances and settling the basis of the area of Automated Analysis of Feature Models (AAFM). From then on, different studies have applied the AAFM in different domains. In this paper, we provide an overview of the evolution of this field since 2010 by performing a systematic mapping study considering 423 primary sources. We found six different variability facets where the AAFM is being applied that define the tendencies: product configuration and derivation; testing and evolution; reverse engineering; multi-model variability-analysis; variability modelling and variability-intensive systems. We also confirmed that there is a lack of industrial evidence in most of the cases. Finally, we present where and when the papers have been published and who are the authors and institutions that are contributing to the field. We observed that the maturity is proven by the increment in the number of journals published along the years as well as the diversity of conferences and workshops where papers are published. We also suggest some synergies with other areas such as cloud or mobile computing among others that can motivate further research in the future.Ministerio de Economía y Competitividad TIN2015-70560-RJunta de Andalucía TIC-186

On SAT Technologies for dependency management and beyond

International audienceSAT solvers technology is now mature enough to be part of the engineer toolbox side by side with Mixed Integer Programming and Constraint Programming tools. As of June 2008, two great pieces of software are using SAT technology to manage dependency like problems: the open source Linux distribution OpenSuse 11.0, released on June 19, 2008, integrates a custom SAT solver in their dependency manager Zypp. The new update manager of Eclipse 3.4, called Equinox p2, also uses SAT technology to resolve dependencies in their OSGi platform. The use of SAT technology in Software Product Lines has already been pointed out by several authors. We believe that the current interest for solving dependency management problems in SAT technologies opens quite interesting challenges to the SAT community. First, since those problems are met in software with interactive use, SAT engines need to solve them within seconds. Second, providing one solution is usually not sufficient: finding the best solution is usually what users want. Finally, fully supported open source or commercial SAT engines are needed for a broader adoption in the software engineering community

Some Challenges of Feature-based Merging of Class Diagrams

In software product line engineering, feature mod-els enable to automate the generation of product-specific models in conjunction with domain “base models ” (e.g. UML models). Two approaches ex-ist: pruning of a large domain model, or merging of model fragments. In this paper, we investigate the impact of the merging approach on base mod-els, and how they are made and used. We adopt an empirical method and test the approach on an ex-ample. The results show several challenges in the way model fragments are written, the need for new modelling language constructs and tool support. 1

Un analizador de modelos de variabilidad basado en el árbol de características.

Un árbol de características generalizado (GFT) es un modelo de variabilidad en el que las restricciones textuales han sido eliminadas manteniendo la semántica del modelo. La ventaja de un GFT es que se puede analizar directamente razonando sobre las relaciones jerárquicas del árbol de características, sin tener que transformar el modelo a SAT o construir un árbol de decisión binario (BDD). Las desventajas de un GFT son que puede contener características duplicadas y que su tamaño en número de características con respecto al modelo de variabilidad original es considerablemente mayor, lo que complica el análisis automático. En este artículo se propone un analizador de modelos GFT basado en las relaciones jerárquicas del árbol de características teniendo en cuenta la existencia de características duplicadas. Se definen un conjunto de operaciones de análisis sobre GFT y se compara su eficiencia con solvers SAT y BDD. El solver GFT mejora la eficiencia del análisis sobre solvers BDD para modelos de hasta diez mil características.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Realising Variability in Dynamic Software Product Line Solutions

Modern systems need to be able to self-adapt to changes in user needs, and changes affecting the system itself or its environment. Dynamic software product line (DSPL) is an engineering approach for developing self-adaptive systems based on commonalities and variabilities for a family of similar systems. Currently, many DSPL approaches fail to meet all adaptability requirements, and in many cases, they are developed in a such unstructured manner that the controller is not explicitly represented, for example. We specify a two-dimension taxonomy to address basic technical issues for realising variability in DSPLs. The self-adaptation dimension classifies the different design choices for the adaptability requirements. The DSPL variability dimension classifies different design choices for implementing variability schemes and for creating different kinds of feature models. Our study was substantiated by surveying several DSPL approaches, and evaluating and comparing their different design strategies. We also summarise practical issues and difficulties, identify major trends in actual DSPL proposals, and suggest directions for future