Resultados de búsqueda para software product lines

With a volatile labour and technological market, onboarding is becoming increasingly important. The process of incorporating a new developer, a.k.a. the newcomer, into a software development team is reckoned to be lengthy, frustrating and expensive. Newcomers face personal, interpersonal, process and technical barriers during their incorporation, which, in turn, aects the overall productivity of the whole team. This problem exacerbates for Software Product Lines (SPLs), where their size and variability combine to make onboarding even more challenging, even more so for developers that are transferred from the Application Engineering team into the Domain Engineering team, who will be our target newcomers. This work presents concept maps on the role of sensemaking scaolds to help to introduce these newcomers into the SPL domain. Concept maps, used as knowledge visualisation tools, have been proven to be helpful for meaningful learning. Our main insight is to capture concepts of the SPL domain and their interrelationships in a concept map, and then, present them incrementally, helping newcomers grasp the SPL and aiding them in exploring it in a guided manner while avoiding information overload. This work’s contributions are four-fold. First, concept maps are proposed as a representation to introduce newcomers into the SPL domain. Second, concept maps are presented as the means for a guided exploration of the SPL core assets. Third, a feature-driven concept map construction process is introduced. Last, the usefulness of concept maps as guides for SPL onboarding is tested through a formativeevaluation.Link to the online demo: https://rebrand.ly/wacline-cmap

Las líneas de productos de software (Software Product Line, SPL) permiten la reutilización sistemática dentro de una organización, lo que permite reducir los costes, los esfuerzos, el tiempo de desarrollo y el número medio de defectos por producto. Sin embargo, no existen evidencias empíricas sobre la adopción de las SPL en las empresas de desarrollo software, para la personalización de sus productos. Para evaluar la necesidad de las tecnologías SPL en el desarrollo software real es necesario analizar las prácticas de variabilidad en las empresas para desarrollar sus productos, señalando las fortalezas y debilidades de sus enfoques.Para ello, presentamos el diseño de un estudio para evaluar cómo las empresas realizan la gestión de la variabilidad. Partimos de la base de que la mayoría de las empresas gestionan la variabilidad, pero no muchas de ellas conocen las líneas de productos de software.

The adoption of Software Product Line Engineering (SPLE) is usually only based on its theoretical benefits instead of empirical evidences. In fact, there is no work that synthesizes the empirical studies on SPLE. This makes it difficult for researchers to base their contributions on previous works validated with an empirical strategy. The objective of this work is to discover and summarize the studies that have used empirical evidences in SPLE limited to those ones with the intervention of humans. This will allow evaluating the quality and to know the scope of these studies over time. Doing so, research opportunities can arise. A systematic literature review was conducted. The scope of the work focuses on those studies in which there is human intervention and were published between 2000 and 2018. We considered peer-reviewed papers from journals and top software engineering conferences. Out of a total of 1880 studies in the initial set, a total of 62 primary studies were selected after applying a series of inclusion and exclusion criteria. We found that, approximately 56+AFwAJQ of the studies used the empirical case study strategy while the rest used experimental strategies. Around 86+AFwAJQ of the case studies were performed in an industrial environment showing the penetration of SPLE in industry. The interest of empirical studies has been growing since 2008. Around 95.16+AFwAJQ of the studies address aspects related to domain engineering while application engineering received less attention. Most of the experiments and case study evaluated showed an acceptable level of quality. The first study found dates from 2005 and since then, the interest in the empirical SPLE has increased.

A Software Product Line (SPL) is a set of products builtfrom a number of features, the set of valid products being dened bya feature model. Typically, it does not make sense to test all productsdened by an SPL and one instead chooses a set of products to test(test selection) and, ideally, derives a good order in which to test them(test prioritisation). Since one cannot know in advance which productswill reveal faults, test selection and prioritisation are normally based onobjective functions that are known to relate to likely effectiveness orcost. This article introduces a new technique, the grid-based evolutionstrategy (GrES), which considers several objective functions that assessa selection or prioritisation and aims to optimise on all of these. Theproblem is thus a many-objective optimisation problem. We use a newapproach, in which all of the objective functions are considered but one(pairwise coverage) is seen as the most important. We also derive a novelevolution strategy based on domain knowledge. The results of the evalua-tion, on randomly generated and realistic feature models, were promising,with GrES outperforming previously proposed techniques and a range ofmany-objective optimisation algorithms.

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.

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.

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.

-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

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.

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