Development of Digital Libraries with Software Product Line Engineering

Digital Libraries have become popular nowadays since important libraries all over the world started distributing their collections online, properly classified, and, in many cases, with access to the digital version of the resource. These programs have been beneficial to the general population as well as research groups in fields such as language and literature. Nonetheless, since their creation is a time-consuming and costly process, small organizations are forced to rely on obsolete or poorly designed software. However, most of the features, including the data model, are shared by this type of system, with minor variations depending on the type of resources to be handled. This article presents a Software Product Line (SPL) for the semi-automatic generation of Digital Libraries (DL). Our SPL allows developers to specify which DL features are required, which will define the data model variationand the generated source code. The specification is then transformed into a fully functional DL application with the specified features that is ready for deployment. We present the feature model, the SPL implementation, and acase study on three sample projects that enabled us to evaluate the resulting software, with a focus on development effort savings.

Properties of a Feature in Code-Assets: An Exploratory Study

Software product line engineering is a paradigm for developing a family of software products from a repository of reusable assets rather than developing each individual product from scratch. In featureoriented software product line engineering, the common and the variable characteristics of the products are expressed in terms of features. Using software product line engineering approach, software products are produced en masse by means of two engineering phases: (i) Domain Engineering and, (ii) Application Engineering. At the domain engineering phase, reusable assets are developed with variation points where variant features may be bound for each of the diverse products. At the application engineering phase, individual and customized products are developed from the reusable assets. Ideally, the reusable assets should be adaptable with less effort to support additional variations (features) that were not planned beforehand in order to increase the usage context of SPL as a result of expanding markets or when a new usage context of software product line emerges. This paper presents an exploration research to investigate the properties of features, in the code-asset implemented using Object-Oriented Programming Style. In the exploration, we observed that program elements of disparate features formed unions as well as intersections that may affect modifiability of the code-assets. The implication of this research to practice is that an unstable product line and with the tendency of emerging variations should aim for techniques that limit the number of intersections between program elements of different features. Similarly, the implication of the observation to research is that there should be subsequent investigations using multiple case studies in different software domains and programming styles to improve the understanding of the findings.

Análisis Automático de Modelos de Variabilidad : el Proceso SeVaTax

Una línea de productos software provee de una plataforma común flexible, de manera que permita adaptarse a las diferentes necesidades de productos dentro de un rango de requerimientos establecido. Dicha flexibilidad se logra mediante la identificación, definición y posterior configuración de lo que se conoce como Variabilidad. Los modelos de variabilidad, como cualquier otro artefacto software, están sujetos a un proceso de análisis para detectar y (posiblemente) resolver errores e incompatibilidades. Esto lleva a la existencia de un proceso de análisis de variabilidad, que presta especial atención al momento de definición y uso de la variabilidad. Existen hoy día, propuestas que presentan diferentes métodos y/o herramientas para realizar un análisis automatizado de la variabilidad. Sin embargo, muchas de ellas se enfocan en sólo un tipo de modelo como entrada y/o sólo disponen de algunos escenarios de validación para controlar. A su vez, muy pocas proponen correcciones o identifican exactamente dónde se encuentran las anomalías o inconsistencias en los modelos. Entonces, se hace necesario mejorar este proceso de validación y su soporte, evaluando el rendimiento durante esa validación. En este sentido, esta Tesis propone el proceso llamado SeVaTax, que toma como entrada modelos de variabilidad (uno o más), generando una representación formal que permite analizar un conjunto de escenarios de validación mayor y proporciona un nivel diferente de respuestas, incluso proponiendo algunas acciones específicas para corregir los modelos. Se proponen dieciocho escenarios de validación, que son experimentalmente validados desde dos puntos de vista: (1) la exactitud de los resultados en términos de los errores que SeVaTax permite identificar; y (2) el cubrimiento, que muestra el grado en que el conjunto de escenarios está cubierto por otros enfoques con herramientas similares. A software product line supplies a common and flexible platform, which allows to adaptto different needs of products from a range of established requirements. Such a flexibility is achieved through the identification, definition and configuration of what is called Variability. Variability models, like any other software artifact, are subjected to an analysis process to detect and (possibly) solve errors and incompatibilities. This fact leads to the existence of a process called variability analysis, which pays special attention to the variability definition and use. Nowadays, several approaches propose different methods and/or tools to automatically analyzing variability. However, many of these approaches only focus on one type of model as input, and/or only show some validation scenarios to control. In addition, few approaches propose corrections, or identify where the anomalies or inconsistencies are. Therefore, there is a need of improving the analysis process as well as its support, assessing their performance during validation. In this sense, this Thesis proposes the SeVaTax process, which takes variability models (one or more) as inputs, generates a formal representation that allows to analyze a larger set of validation scenarios, and gives a different level of responses to validation – including corrections in some cases. Eighteen validation scenarios are proposed, which are experimentally validated form two viewpoints: (1) accuracy, in terms of errors that SeVaTax identifies; and (2) covering, that shows the degree in which the set of scenarios is covered by similar proposals in the literature.