VMTools-RA: a Reference Architecture for Software Variability Tools

Currently, software systems must be appropriately developed to support an amount of variability for accommodating different requirements. To support such development, a diversity of tools has already been designed for variability management (i.e., identification, modeling, evaluation, and realization). However, due to this diversity, there is a lack of consensus on what in fact software variability tools are and even what functionalities they should provide. Besides that, the building of new tools is still an effort- and time-consuming task. To support their building, we present VMTools-RA, a reference architecture that encompasses knowledge and practice for developing and evolving variability tools. Designed in a systematic way, VMTools-RA was evaluated throughout: a controlled experiment with software developer practitioners; and an instantiation of the VMTools-RA architecture to implement a software variability tool, named SMartyModeling. As a result, VMTools-RA is evidenced to be feasible and it can be considered an important contribution to the software variability and developers of variability-intensive software systems community, which require specific tools developed in a faster manner with less risk, what a reference architecture could provide

Development and Evaluation of a Software Product Line for M-Learning Applications

The popularity of mobile devices in all social classes has motivated the development of mobile learning (m-learning) applications. The existing applications, even having many benefits and facilities in relation to the teaching-learning process, still presents problems and challenges, es- pecially regarding the development, reuse and architectural standardization. Particularly, there is a growing adoption of the Software Product Line (SPL) concept, in view of research that investigates these gaps. This paradigm enables organizations to explore the similarities and variabilities of their products, increasing the reuse of artifacts and, consequently, reducing costs and development time. In this context, we discuss how systematic reuse can improve the development of solutions in the m-learning domain. Therefore, this work presents the design, development and experimental evaluation of M-SPLearning, an SPL created to enable the systematic production of m-learning applications. Specifically, the conception of M-SPLearning covers from the initial study for an effective domain analysis to the implementation and evaluation of its functional version. In this regard, the products have been experimentally evaluated by industry software developers, pro- viding statistical evidence that the use of our SPL can speed up the time-to-market of m-learning applications, in addition to reducing their respective number of faults

Have Variability Tools Fulfilled the Needs of the Software Industry?

For nearly 30 years, industry and researchers have proposed many software variability tools to cope with the complexity of modeling variability in software development, followed by a number of publications on variability techniques built upon theoretical foundations. After more than 25 years of the practice of software variability, there are not many studies investigating the impact of software variability tools in the industry and the perception of practitioners. For this reason, we investigate in this research work how existing software variability tools fulfill the needs of companies demanding this kind of tool support. We conducted a survey with practitioners from companies in eight different countries in order to analyze the missing capabilities of software variability management tools and we compared the results of the survey with the scientifoc literature through a systematic mapping study (SMS) to analyze if the proposed solutions cover the needs required by practitioners. Our major findings indicate that many tools lack important qualities such as interoperability, collaborative work, code generation, scalability, impact analysis, and test; while the results from the SMS showed these such capabilities are, to some extent, found in some of the existing tools

Pacote Experimental - SMarty vs. PLUS - Casos de Uso - Geração de Configurações

<p>Pacote Experimental - SMarty vs. PLUS - Casos de Uso - Geração de Configurações</p