A domain specific language for domotic systems

To cope with modernity, the interesting of having a fully automated house has been increasing over the years, as technology evolves and as our lives become more stressful and overloaded. An automation system provides a way to simplify some daily tasks, allowing us to have more spare time to perform activities where we are really needed. There are some systems in this domain that try to implement these characteristics, but this kind of technology is at its early stages of evolution being that it is still far away of empowering the user with the desired control over a habitation. The reason is that the mentioned systems miss some important features such as adaptability, extension and evolution. These systems, developed from a bottom-up approach, are often tailored for programmers and domain experts, discarding most of the times the end users that remain with unfinished interfaces or products that they have difficulty to control. Moreover, complex behaviors are avoided, since they are extremely difficult to implement mostly due to the necessity of handling priorities, conflicts and device calibration. Besides, these solutions are only reachable at very high costs, yet they still have the limitation of being difficult to configure by non-technical people once in runtime operation. As a result, it is necessary to create a tool that allows the execution of several automated actions, with an interface that is easy to use but at the same time supports all the main features of this domain. It is also desirable that this tool is independent of the hardware so it can be reused, thus a Model Driven Development approach (MDD) is the ideal option, as it is a method that follows those principles. Since the automation domain has some very specific concepts, the use of models should be combined with a Domain Specific Language (DSL). With these two methods, it is possible to create a solution that is adapted to the end users, but also to domain experts and programmers due to the several levels of abstraction that can be added to diminish the complexity of use. The aim of this thesis is to design a Domain Specific Language (DSL) that uses the Model Driven Development approach (MDD), with the purpose of supporting Home Automation (HA) concepts. In this implementation, the development of simple and complex scenarios should be supported and will be one of the most important concerns. This DSL should also support other significant features in this domain, such as the ability to schedule tasks, which is something that is limited in the current existing solutions.

Regret associated with past and future messes under a maximizing mind-set

Promotions can make you happy if you get the “best” deal or miserable if you miss it. Previous research on this topic has shown that people favor products associated with a past miss to products associated with a future miss, and people in a maximizing mind-set, i.e. people who search for the best in different domains, feel more regret in a consumption domain. This research confirms that consumers prefer purchasing a product associated with a past miss (Experiments 1 and 2) and that regret levels are higher when participants come across the future miss, under the maximizing mind-set (Experiment 2). These studies add to the notion that information on regret might prompt people to make decisions towards a more optimistic outcome.

Choosing between past and future regret

Sometimes decisions imply trade-offs that force people to accept missing an opportunity in the past or in the future. It has not yet been clarified whether a past miss or a future miss elicits more regret. In a direct comparison, Shani, Danziger, and Zeelenberg found support for the greater impact of future misses. In an experimental design with 216 students, we replicated their study and tested the strength of the future miss in a separate evaluation and with different periods. The results show that future misses cause less regret than past misses do when evaluated separately. However, future misses made participants change their feelings of regret more than past misses did. Feelings of regret did not decrease when future misses were further away. Our findings support the strength of future misses on regret but also show contrasting effects when evaluated separately. This indicates the further need for research in this topic.