Abstract. Context: Model-Driven Development (MDD) is a paradigm that prescribes building conceptual models that abstractly represent the system and generating code from these models through transformation rules. The literature is rife with claims about the benefits of MDD, but they are hardly supported by evidences. Objective: This experimental investigation aims to verify some of the most cited benefits of MDD. Method: We run an experiment on a small set of classes using student subjects to compare the quality, effort, productivity and satisfaction of traditional development and MDD. The experiment participants built two web applications from scratch, one where the developers implement the code by hand and another using an industrial MDD tool that automatically generates the code from a conceptual model. Results: Outcomes show that there are no significant differences between both methods with regard to effort, productivity and satisfaction, although quality in MDD is more robust to small variations in problem complexity. We discuss possible explanations for these results. Conclusions: For small systems and less programming-experienced subjects, MDD does not always yield better results than a traditional method, even regarding effort and productivity. This contradicts some previous statements about MDD advantages. The benefits of developing a system with MDD appear to depend on certain characteristics of the development context.

Refactoring has been reported as a helpful technique to systematically improve nonfunctional attributes of software. This paper evaluates the relevance of refactoring for improving usability on web applications. We conducted an experiment with two replications at different locations, with subjects of different profiles. Objects chosen for the experiment were two e-commerce applications that exhibit common business processes in today's web usage. Through the experiment we found that half of the studied refactorings cause a significant improvement in usability. The rest of the refactorings required a post-hoc analysis in which we Empir Software Eng considered aspects like user expertise in the interaction with web applications or type of application. We conclude that, when improving quality in use, the success of the refactoring process depends on several factors, including the type of software system, context and users. We have analyzed all these aspects, which developers must consider for a better decision support at the time of prioritizing improvements and outweighing effort.

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Usability is currently a key feature for developing quality systems. A system that satisfies all the functional requirements can be strongly rejected by end-users if it presents usability problems. End-users demand intuitive interfaces and an easy interaction in order to simplify their work. The first step in developing usable systems is to determine whether a system is or is not usable. To do this, there are several proposals for measuring the system usability. Most of these proposals are focused on the final system and require a large amount of resources to perform the evaluation (end-users, video cameras, questionnaires, etc.). Usability problems that are detected once the system has been developed involve a lot of reworking by the analyst since these changes can affect the analysis, design, and implementation phases. This paper proposes a method to minimize the resources needed for the evaluation and reworking of usability problems. We propose an early usability evaluation that is based on conceptual models. The analyst can measure the usability of attributes that depend on conceptual primitives. This evaluation can be automated taking as input the conceptual models that represent the system abstractly.

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Context: Nowadays, there are sound methods and tools which implement the Model-Driven Develop-ment approach (MDD) satisfactorily. However, MDD approaches focus on representing and generating code that represents functionality, behaviour and persistence, putting the interaction, and more specifically the usability, in a second place. If we aim to include usability features in a system developed with a MDD tool, we need to extend manually the generated code. Objective: This paper tackles how to include functional usability features (usability recommendations strongly related to system functionality) in MDD through conceptual primitives. Method: The approach consists of studying usability guidelines to identify usability properties that can be represented in a conceptual model. Next, these new primitives are the input for a model compiler that generates the code according to the characteristics expressed in them. An empirical study with 66 subjects was conducted to study the effect of including functional usability features regarding end users' satisfaction and time to complete tasks. Moreover, we have compared the workload of two MDD analysts including usability features by hand in the generated code versus including them through conceptual primitives according to our approach. Results: Results of the empirical study shows that after including usability features, end users' satisfac-tion improves while spent time does not change significantly. This justifies the use of usability features in the software development process. Results of the comparison show that the workload required to adapt the MDD method to support usability features through conceptual primitives is heavy. However, once MDD supports these features, MDD analysts working with primitives are more efficient than MDD analysts implementing these features manually. Conclusion: This approach brings us a step closer to conceptual models where models represent not only functionality, behaviour or persistence, but also usability features.

Abstract. MDD tools are very useful to draw conceptual models and to automate code generation. Even though this would bring many benefits, wide adoption of MDD tools is not yet a reality. Various research activities are being undertaken to find why and to provide the required solutions. However, insufficient research has been done on a key factor for the acceptance of MDD tools: usability. With the help of end-users, this paper presents a framework to evaluate the usability of MDD tools. The framework will be used as a basis for a family of experiments to get clear insights into the barriers to usability that prevent MDD tools from being widely adopted in industry. To illustrate the applicability of our framework, we instantiated it for performing a usability evaluation of a tool named INTEGRANOVA. Furthermore, we compared the outcome of the study with another usability evaluation technique based on ergonomic criteria.

The Big Data domain offers valuable opportunities to gain valuable knowledge. The User Interface (UI), the place where the user interacts to extract knowledge from data, must be adapted to address the domain complexities. Designing UIs for Big Data becomes a challenge that involves identifying and designing the user-data interaction implicated in the knowledge extraction. To design such an interaction, one widely used approach is design patterns. Design Patterns describe solutions to common interaction design problems. This paper proposes a set of patterns to design UIs aimed at extracting knowledge from the Big Data systems' data conceptual schemas. As a practical example, we apply the patterns to design UI's for the Diagnosis of Genetic Diseases domain since it is a clear case of extracting knowledge from a complex set of genetic data. Our patterns provide valuable design guidelines for Big Data UIs.