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

Debian Packages Repositories as Software Product Line Models. Towards Automated Analysis

The automated analysis of variability models in general and feature models in particular is a thriving research topic. There have been numerous contributions along the last twenty years in this area including both, research papers and tools. However, the lack of realistic variability models to evaluate those techniques and tools is recognized as a major problem by the community. To address this issue, we looked for large– scale variability models in the open source community. We found that the Debian package dependency language can be interpreted as software product line variability model. Moreover, we found that those models can be automatically analysed in a software product line variability model-like style. In this paper, we take a first step towards the automated analysis of Debian package dependency language. We provide a mapping from these models to propositional formulas. We also show how this could allow us to perform analysis operations on the repositories like the detection of anomalies (e.g. packages that cannot be installed).CICYT TIN2009- 07366Junta de Andalucía TIC-253

An automated Model-based Testing Approach in Software Product Lines Using a Variability Language.

This paper presents the application of an automated testing approach for Software Product Lines (SPL) driven by its state-machine and variability models. Context: Model-based testing provides a technique for automatic generation of test cases using models. Introduction of a variability model in this technique can achieve testing automation in SPL. Method: We use UML and CVL (Common Variability Language) models as input, and JUnit test cases are derived from these models. This approach has been implemented using the UML2 Eclipse Modeling platform and the CVL-Tool. Validation: A model checking tool prototype has been developed and a case study has been performed. Conclusions: Preliminary experiments have proved that our approach can find structural errors in the SPL under test. In our future work we will introduce Object Constraint Language (OCL) constraints attached to the input UML mode

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

Supporting the grow-and-prune model for evolving software product lines

207 p.Software Product Lines (SPLs) aim at supporting the development of a whole family of software products through a systematic reuse of shared assets. To this end, SPL development is separated into two interrelated processes: (1) domain engineering (DE), where the scope and variability of the system is defined and reusable core-assets are developed; and (2) application engineering (AE), where products are derived by selecting core assets and resolving variability. Evolution in SPLs is considered to be more challenging than in traditional systems, as both core-assets and products need to co-evolve. The so-called grow-and-prune model has proven great flexibility to incrementally evolve an SPL by letting the products grow, and later prune the product functionalities deemed useful by refactoring and merging them back to the reusable SPL core-asset base. This Thesis aims at supporting the grow-and-prune model as for initiating and enacting the pruning. Initiating the pruning requires SPL engineers to conduct customization analysis, i.e. analyzing how products have changed the core-assets. Customization analysis aims at identifying interesting product customizations to be ported to the core-asset base. However, existing tools do not fulfill engineers needs to conduct this practice. To address this issue, this Thesis elaborates on the SPL engineers' needs when conducting customization analysis, and proposes a data-warehouse approach to help SPL engineers on the analysis. Once the interesting customizations have been identified, the pruning needs to be enacted. This means that product code needs to be ported to the core-asset realm, while products are upgraded with newer functionalities and bug-fixes available in newer core-asset releases. Herein, synchronizing both parties through sync paths is required. However, the state of-the-art tools are not tailored to SPL sync paths, and this hinders synchronizing core-assets and products. To address this issue, this Thesis proposes to leverage existing Version Control Systems (i.e. git/Github) to provide sync operations as first-class construct

The KB paradigm and its application to interactive configuration

The knowledge base paradigm aims to express domain knowledge in a rich formal language, and to use this domain knowledge as a knowledge base to solve various problems and tasks that arise in the domain by applying multiple forms of inference. As such, the paradigm applies a strict separation of concerns between information and problem solving. In this paper, we analyze the principles and feasibility of the knowledge base paradigm in the context of an important class of applications: interactive configuration problems. In interactive configuration problems, a configuration of interrelated objects under constraints is searched, where the system assists the user in reaching an intended configuration. It is widely recognized in industry that good software solutions for these problems are very difficult to develop. We investigate such problems from the perspective of the KB paradigm. We show that multiple functionalities in this domain can be achieved by applying different forms of logical inferences on a formal specification of the configuration domain. We report on a proof of concept of this approach in a real-life application with a banking company. To appear in Theory and Practice of Logic Programming (TPLP).Comment: To appear in Theory and Practice of Logic Programming (TPLP

Domain Specific Languages for Managing Feature Models: Advances and Challenges

International audienceManaging multiple and complex feature models is a tedious and error-prone activity in software product line engineering. Despite many advances in formal methods and analysis techniques, the supporting tools and APIs are not easily usable together, nor unified. In this paper, we report on the development and evolution of the Familiar Domain-Specific Language (DSL). Its toolset is dedicated to the large scale management of feature models through a good support for separating concerns, composing feature models and scripting manipulations. We overview various applications of Familiar and discuss both advantages and identified drawbacks. We then devise salient challenges to improve such DSL support in the near future

Visualizing the customization endeavor in product-based-evolving software product lines: a case of action design research

[EN] Software Product Lines (SPLs) aim at systematically reusing software assets, and deriving products (a.k.a., variants) out of those assets. However, it is not always possible to handle SPL evolution directly through these reusable assets. Time-to-market pressure, expedited bug fixes, or product specifics lead to the evolution to first happen at the product level, and to be later merged back into the SPL platform where the core assets reside. This is referred to as product-based evolution. In this scenario, deciding when and what should go into the next SPL release is far from trivial. Distinct questions arise. How much effort are developers spending on product customization? Which are the most customized core assets? To which extent is the core asset code being reused for a given product? We refer to this endeavor as Customization Analysis, i.e., understanding the functional increments in adjusting products from the last SPL platform release. The scale of the SPLs' code-base calls for customization analysis to be conducted through Visual Analytics tools. This work addresses the design principles for such tools through a joint effort between academia and industry, specifically, Danfoss Drives, a company division in charge of the P400 SPL. Accordingly, we adopt an Action Design Research approach where answers are sought by interacting with the practitioners in the studied situations. We contribute by providing informed goals for customization analysis as well as an intervention in terms of a visual analytics tool. We conclude by discussing to what extent this experience can be generalized to product-based evolving SPL organizations other than Danfoss Drives.Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This work is supported by the Spanish Ministry of Science, Innovation and Universities grant number RTI2018099818-B-I00 and MCIU-AEI TIN2017-90644-REDT (TASOVA). ONEKIN enjoys support from the program 'Grupos de Investigacion del Sistema Univesitario Vasco 2019-2021' under contract IT1235-19. Raul Medeiros enjoys a doctoral grant from the Spanish Ministry of Science and Innovation

Improving Variabilty Analysis through Scenario-Based Incompatibility Detection

Software Product Line (SPL) developments include Variability Management (VA) as a core activity aiming at minimizing the inherent complexity in commonality and variability manipulation. Particularly, the (automated) analysis of variability models refers to the activities, methods and techniques involved in the definition, design, and instantiation of variabilities modeled during SPL development. Steps of this analysis are defined as a variability analysis process (VA process), which is focused on assisting variability model designers in avoiding anomalies and/or inconsistencies, and minimizing problems when products are implemented and derived. Previously, we have proposed an approach for analyzing variability models through a well-defined VA process (named SeVaTax). This process includes a comprehensive set of scenarios, which allows a designer to detect (and even correct in some cases) different incompatibilities. In this work, we extend SeVaTax by classifying the scenarios according to their dependencies, and by assessing the use of these scenarios. This assessment introduces two experiments to evaluate accuracy and coverage. The former addresses responses when variability models are analyzed, and the latter the completeness of our process with respect to other proposals. Findings show that a more extensive set of scenarios might improve the possibilities of current practices in variability analysis.Fil: Buccella, Agustina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Confluencia; Argentina. Universidad Nacional del Comahue. Facultad de Informatica; ArgentinaFil: Pol'la, Matias Esteban. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Confluencia; Argentina. Universidad Nacional del Comahue. Facultad de Informatica; ArgentinaFil: Cechich, Susana Alejandra. Universidad Nacional del Comahue. Facultad de Informatica; Argentin