Many businesses depend on legacy systems, which often use outdated technology that complicates maintenance and updates. Therefore, software modernization is essential, particularly data migration between different database schemas. Established methodologies, like model transformation and ETL tools, facilitate this migration. However, these methodologies require deep knowledge of database languages and both the source and target schemas. This necessity renders data migration an error-prone and cognitively demanding task. Our objective is to alleviate developers’ workloads during schema evolution by proposing DAMI-Framework. This framework incorporates a domain-specific language (DSL) and a parser to facilitate data migration between database schemas. DAMI-DSL simplifies schema mapping, while the parser automates SQL script generation. To evaluate DAMI-Framework, we conducted an empirical evaluation with 21 developers to assess their experiences using our DSL versus traditional SQL. The study allows us to measure their perceptions of the DSL properties and user experience. The participants praised DAMI-DSL for its readability and ease of use. The findings indicate that our framework has positive impact in data migration efforts compared to SQL scripts, by reducing the lines of code and characters required for the migration by 18.3% and 35.6%, respectively.

Software Product Lines (SPL) enable the creation of software product families with shared core components using feature models to model variability. Choosing features from a feature model to generate a product may not be sufficient in certain situations because the application engineer may need to be able to decide on configuration time the system’s elements to which a certain feature will be applied. Therefore, there is a need to select which features have to be included in the product but also to which of its elements they have to be applied. We introduce local features that are selectively applied to specific parts of the system during product configuration. We formalize local features using multimodels to establish relationships between local features and other elements of the system models. The paper includes examples illustrating the motivation for local features, a formal definition, and a domain-specific language for specification and implementation. Finally, we present a case study in a real scenario that shows how the concept of local features allowed us to define the variability of a complex system. The examples and the application case show that the proposal achieves higher customization levels at the application engineering phase.

Abstract DevOps has emerged as a practical approach to the interaction between development and operations. This approach has been extended to the interaction with business functions, generating the term BizDevOps. Although many proposals and tools support BizDevOps from a technical viewpoint, there has been no significant improvement in management aspects, such as evaluating the practices and processes involved in the area. This paper presents two case studies on the assessment of BizDevOps practices using MMBDO (Maturity Model for BizDevOps), a maturity model for BizDevOps based on international ICT standards. The case studies were conducted in two organizations with different profiles: a large multinational ICT company with a unit specialized in providing DevOps to the rest of the company and a small software development company that implements DevOps practices as part of its development system. The evidence we obtained in the case studies supports the adequacy of MMBDO for assessing the maturity of BizDevOps in real companies. Also, the combination of the two case studies supports the adequacy of the model for being used in companies with different sizes and levels of maturity. MMBDO is an adequate proposal for assessing the maturity of BizDevOps in software organizations and a suitable tool for process improvement.

Abstract Even though different applications based on Geographic Information Systems (GIS) provide different features and functions, they all share a set of common concepts (e.g., spatial data types, operations, services), a common architecture, and a common set of technologies. Furthermore, common structures appear repeatedly in different GIS, although they have to be specialized in specific application domains. Multilevel modeling is an approach to model-driven engineering (MDE) in which the number of metamodel levels is not fixed. This approach aims at solving the limitations of a two-level metamodeling approach, which forces the designer to include all the metamodel elements at the same level. In this paper, we address the application of multilevel modeling to the domain of GIS, and we evaluate its potential benefits. Although we do not present a complete set of models, we present four representative scenarios supported by example models. One of them is based on the standards defined by ISO TC/211 and the Open Geospatial Consortium. The other three are based on the EU INSPIRE Directive (territory administration, spatial networks, and facility management). These scenarios show that multilevel modeling can provide more benefits to GIS modeling than a two-level metamodeling approach.

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.

In this paper, we present a declarative domain-specific language (DSL) for the development of Geographic Information Systems (GIS). GIS applications manage information with a spatial component, usually in the form of points, lines, polygons, or variants of these basic data types, in domains where the spatial information plays a central role. They provide the user with different functionalities on different application domains, but they are usually developed according to a common architecture and using a common set of technologies. Hence, they share a significant number of elements that make some aspects of their development quite repetitive. Our DSL allows developers to specify the entities, geographic layers, and maps of the applications using a declarative language. Then, the specification is transformed into a working GIS application. We present the language, its implementation, and a case study on two sample projects that allowed us to evaluate the resulting software, paying special attention to the savings in the development effort.

Abstract One of the main challenges of software testing research is the automated addition of oracles to the generated test cases: Whereas the automated generation of operation sequences (which is one of the essential components of test cases) is in practice a solved problem, the automated addition of the oracle (another indispensable element) is still an important problem and an open research question. This article proposes an approach to get executable test suites composed by complete test cases (i.e., they include the oracle). The core of the method is based on annotated regular expressions. The test generation process, which is supported by a tool, follows three steps: (1) creation of annotated regular expressions, where each regular expression describes a set of sequences of operations to be executed against the system under test; (2) expansion of the regular expressions to get sequences of operations, which still do not have parameter values; and (3) generation of the executable test cases with oracle. In this third step, each test case is generated with the suitable oracle, depending on the conditions specified in the regular expression.

Geographic information systems (GIS) manage entities with a spatial component (typically, in the form of a point, line, or polygon defined according to a known geographic coordinate system), and provide specific operations to process them, and specific interfaces to visualize them. Although different GIS may provide a completely different set of functionalities, they all share a common set of concepts, architecture, and technologies. Therefore, in the development of GIS there are typically large parts of the system that can be very repetitive. In this paper, we present a domain-specific language to develop GIS from high-level declarative specifications. We present a metamodel for web-based GIS, and a domain-specific language based on that metamodel. We also present a usage example that shows how the language would be used in a real scenario.

Distributing software as a service (SaaS) has become a major trend for web-based systems.However, this software distribution model poses many challenges.One of them is feature variability, that is, some features of the system may be required by some users, but not by all of them.In addition, variability is more complex than just including or excluding a feature, since different types of relationships may exist between features.The implementation of this variability, and the parametrization and configuration of the system can be complex in this context, so the development process of a SaaS system must adequately address variability management.In this paper we present an

Author profiling consists in determining some demographic attributes — such as gender, age, nationality, language, religion, and others — of an author for a given document. This task, which has applications in fields such as forensics, security, or marketing, has been approached from different areas, especially from linguistics and natural language processing, by extracting different types of features from training documents, usually content — and style-based features. In this paper we address the problem by using several compression-inspired strategies that generate different models without analyzing or extracting specific features from the textual content, making them style-oblivious approaches. We analyze the behavior of these techniques, combine them and compare them with other state-of-the-art methods. We show that they can be competitive in terms of accuracy, giving the best predictions for some domains, and they are efficient in time performance.

We present in this paper a web-based version of a scrabble game, describing its architecture and some implementation details. This architecture makes possible a high degree of interactivity, so that the players perceive the game as being played in real-time. Furthermore, no client-side plug-in or applet issued. These properties are achieved by means of a carefully designed architecture that uses AJAX (Asynchronous JavaScript and XMLXML) for data exchange. This architecture guarantees low load on the server, so complex computations relative to the game logic can be done in real-time. Moreover, data structures and algorithms were designed to efficiently access a custom Galician dictionary, which supports the game functionalities. We show in this paper how this data structures and algorithms provide an efficient method to create a Scrabble move generation algorithm. We also show how the combination of these with the architecture proposed provides a fully interactive Web application that can handle complex calculations over a very large lexicon with real-time appearance.

Similarity search is a fundamental operation for applications that deal with unstructured data sources. In this paper we propose a new pivot-based method for similarity search, called sparse spatial selection (SSS). This method guarantees a good pivot selection more efficiently than other methods previously proposed. In addition, SSS adapts itself to the dimensionality of the metric space we are working with, and it is not necessary to specify in advance the number of pivots to extract. Furthermore, SSS is dynamic, it supports object insertions in the database efficiently, it can work with both continuous and discrete distance functions, and it is suitable for secondary memory storage. In this work we provide experimental results that confirm the advantages of the method with several vector and metric spaces