Abstract
This paper presents a graphical interface to query model-driven spreadsheets to simplify query construction for typical end-users with little to no knowledge of SQL. This was based on experience with previous work and empirical studies in querying systems. We briefly show our previous text based model-driven querying system. Afterwards, we detail our graphical model-driven querying interface, explaining each part of the interface and showing an example. To validate our work, we executed an empirical study, comparing our graphical querying approach to an alternative querying tool, which produced positive results.

Abstract
The analytical methods based on evaluation models of interactive systems were proposed as an alternative to user testing in the last stages of the software development due to its costs. However, the use of isolated behavioral models of the system limits the results of the analytical methods. An example of these limitations relates to the fact that they are unable to identify implementation issues that will impact on usability. With the introduction of model-based testing we are enable to test if the implemented software meets the specified model. This paper presents an model-based approach for test cases generation from the static analysis of source code.

Abstract
Spreadsheets can be seen as a flexible programming environment. However, they lack some of the concepts of regular programming languages, such as structured data types. This can lead the user to edit the spreadsheet in a wrong way and perhaps cause corrupt or redundant data. We devised a method for extraction of a relational model from a spreadsheet and the subsequent embedding of the model back into the spreadsheet to create a model-based spreadsheet programming environment. The extraction algorithm is specific for spreadsheets since it considers particularities such as layout and column arrangement. The extracted model is used to generate formulas and visual elements that are then embedded in the spreadsheet helping the user to edit data in a correct way. We present preliminary experimental results from applying our approach to a sample of spreadsheets from the EUSES Spreadsheet Corpus. Finally, we conduct the first systematic empirical study to assess the effectiveness and efficiency of this approach. A set of spreadsheet end users worked with two different model-based spreadsheets, and we present and analyze here the results achieved.

Abstract
Software refactoring is a well-known technique that provides transformations on software artifacts with the aim of improving their overall quality. In this paper we present a set of refactorings for ClassSheets, a modeling language that allows to specify the business logic of a spreadsheet in an object-oriented fashion. The set of refactorings that we propose allows us to improve the quality of these spreadsheet models. Moreover, it is implemented in a setting that guarantees that all model refactorings are automatically carried to all the corresponding (spreadsheet) instances, thus providing an automatic evolution of the data so it is always synchronized with the model.

Abstract
In the context of an effort to develop methodologies to support the evaluation of interactive system, this paper investigates an approach to detect graphical user interface external bad smells. Our approach consists in detecting user interface external bad smells through model-based reverse engineering from source code. Models are used to define which widgets are present in the interface, when can particular graphical user interface (GUI) events occur, under which conditions, which system actions are executed, and which GUI state is generated next. From these models we obtain metrics that can later be used to identify the smells.

Abstract
This paper presents a study of the runtime, memory usage and energy consumption of twenty seven well-known software languages. We monitor the performance of such languages using ten different programming problems, expressed in each of the languages. Our results show interesting findings, such as, slower/faster languages consuming less/more energy, and how memory usage influences energy consumption. We show how to use our results to provide software engineers support to decide which language to use when energy efficiency is a concern.