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A general approach to Software Product Line testing

Variability is a central concept in Software Product Lines (SPLs). It has been extensively studied how the SPL paradigm can improve both the efficiency of a company and the quality of products. Nevertheless, this brings several challenges when testing an SPL, which are mainly caused by the potentially huge amount of products that can be derived from an SPL. There exist different studies proposing methods for testing SPLs. Also there are secondary studies reviewing and mapping the literature of the existing proposals. Nevertheless, there is a lack of systematic guidelines for practitioners and researchers with the different steps required to perform a testing strategy of an SPL. In this paper, we present a first version of a tutorial that summarizes the existing proposals of the SPL testing area. To the best of our knowledge, there is no similar attempt in existing literature. Our goal is to discuss this tutorial with the community and enrich it to provide a more solid version of it in the future.

Variabilidad en visualización de datos: retos y posibilidades

Los sistemas de visualización de la información nos permiten visualizar datos usando abstracciones de los mismos, por ejemplo, usando gráficos de barras o de tartas. No obstante, la diversidad de visualizaciones dificulta la correcta elecci´on de los sistemas m´as apropiadospara cada conjunto de datos. La ingeniería de líneas de producto y sistemas de alta variabilidad ha generado múltiples técnicas que permiten la configuración óptima de productos software dados unos requisitos o características. En este trabajo proponemos el uso y adaptación de las técnicas de configuración, derivación y análisis automático existentes en el área de líneas de producto software al contexto de la visualización. Permitiendo de esta forma el guiado sobre las opciones de configuración para visualizar un conjunto de datos.

Spectrum-based fault localization in software product lines

Artículo relevante publicado en 2018 en el ISTContext: Software Product Line (SPL) testing is challenging mainly due to the potentially huge number ofproducts under test. Most of the research on this field focuses on making testing affordable by selecting arepresentative subset of products to be tested. However, once the tests are executed and some failures revealed,debugging is a cumbersome and time consuming task due to difficulty to localize and isolate the faulty featuresin the SPL.Objective: This paper presents a debugging approach for the localization of bugs in SPLs.Method: The proposed approach works in two steps. First, the features of the SPL are ranked according to theirsuspiciousness (i.e., likelihood of being faulty) using spectrum-based localization techniques. Then, a novel faultisolation approach is used to generate valid products of minimum size containing the most suspicious features,helping to isolate the cause of failures.Results: For the evaluation of our approach, we compared ten suspiciousness techniques on nine SPLs of differentsizes. The results reveal that three of the techniques (Tarantula, Kulcynski2 and Ample2) stand out over the rest,showing a stable performance with different types of faults and product suite sizes. By using these metrics, faultswere localized by examining between 0.1% and 14.4% of the feature sets.Conclusion: Our results show that the proposed approach is effective at locating bugs in SPLs, serving as a helpfulcomplement for the numerous approaches for testing SPLs.

Improving feature location in long-living model-based product families designed with sustainability goals (YA PUBLICADO)

The benefits of Software Product Lines (SPL) are very appealing: software development becomes better, faster, and cheaper. Unfortunately, these benefits come at the expense of a migration from a family of products to a SPL. Feature Location could be useful in achieving the transition to SPLs. This work presents our FeLLaCaM approach for Feature Location. Our approach calculates similarity to a description of the feature to locate, occurrences where the candidate features remain unchanged, and changes performed to the candidate features throughout the retrospective of the product family. We evaluated our approach in two long-living industrial domains: a model-based family of firmwares for induction hobs that was developed over more than 15 years, and a model-based family of PLC software to control trains that was developed over more than 25 years. In our evaluation, we compare our FeLLaCaM approach with two other approaches for Feature Location: (1) FLL (Feature Location through Latent Semantic Analysis) and (2) FLC (Feature Location through Comparisons). We measure the performance of FeLLaCaM, FLL, and FLC in terms of recall, precision, Matthews Correlation Coefficient, and Area Under the Receiver Operating Characteristics curve. The results show that FeLLaCaM outperforms FLL and FLC.

Artículo Relevante: Reverse engineering language product lines from existing DSL variants.

-Título: Reverse engineering language product lines from existing DSL variants.-Autores: David Méndez-Acuña, José A. Galindo, Benoît Combemale, Arnaud Blouin, Benoit Baudry-Revista de publicación: Journal of Systems and Software-Volumen 133. Noviembre de 2017. Páginas 145-158-DOI: 10.1016/j.jss.2017.05.042Indicios de calidad: JCR-IF: 2,444(22/106).JCR-Q: Q1. JCR-T: T1. JCR-Category/year: COMPUTER SCIENCE, SOFTWARE ENGINEERING – 2016. 9 citas según gscholar

SIP: Optimal Product Selection from Feature Models Using Many-Objective Evolutionary Optimization

Robert M. Hierons, Miqing Li, Xiaohui Liu, Sergio Segura, and Wei Zheng. 2016. SIP: Optimal Product Selection from Feature Models Using Many-Objective Evolutionary Optimization. ACM Trans. Softw. Eng. Methodol. 25, 2, Article 17 (April 2016), 39 pages. DOI: http://dx.doi.org/10.1145/2897760 Indicadores de calidad: – Revista de referencia en el área de Ingeniería del Software (CS-SE: 21/106). – Colaboración internacional con los profesores Robert Hierons [1] y XiaoHui Liu [2]. – Hemos sido invitados a presentar el trabajo en FSE16 e ICSE17 como parte de la iniciativa journal-first (ver programa de la conferencia [3]). – Ha recibido 6 citas desde su publicación en abril de 2016 [4]. [1] http://dblp.uni-trier.de/pers/hd/h/Hierons:Robert_M= [2] http://dblp.uni-trier.de/pers/hd/l/Liu:Xiaohui [2] http://icse2017.gatech.edu/?q=technical-research-accepted [4] https://goo.gl/XyTmQR

Requirement-driven Evolution in Software Product Lines: A Systematic Mapping Study

Artículo relevante. Leticia Montalvillo, Oscar Díaz: Requirement-driven evolution in software product lines: A systematic mapping study. Journal of Systems and Software Volume 122, December 2016, Pages 110-143, COMPUTER SCIENCE, SOFTWARE ENGINEERING, IF: 1,424, Posición: (24/106), Cuartil: Q1. DOI http://dx.doi.org/10.1016/j.jss.2016.08.053

Configurable feature models

Feature models represent all the products that can be built under a variability-intensive system such as a software product line, but they are not fully configurable. There exist no explicit effort in defining configuration models that enable making decisions on attributes and cardinalities in feature models that use these artefacts. In this paper we present configurable feature models as an evolution from feature models that integrate configuration models within, improving the configurability of variability-intensive systems.