Abstract
In an idea generation meeting, the facilitator role is essential to obtain good results. Also the emotional context of the meeting partially determines the (un) success of the meeting, being it of idea generation or decision selection. So the facilitator needs to obtain and process this information in order to assist the participants to reach their goals in different processes of decision making. In this paper is proposed a multi-agent framework able to be used in the support of persons in a affective context-aware and ubiquitous group decision process. Insights of the context-aware model are provided. It allows the gathering of certain typical variables of the affective context (emotions and mood) and transform those values in advises to the facilitator.

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This paper presents a modeling environment (ME) developed for a Domain Specific Language (PARADIGM) which aims to support the construction of models to be used in the context of Model Based GUI Testing (MBGT). It starts by briefly presenting PARADIGM which aims to increase the level of abstraction of the models and promote reuse in order to diminish the effort in building models for MBGT. Afterwards, it describes the architecture of the ME, how the constraints of the language are enforced within the ME to ensure the consistency of the models built, the test case configuration of the model elements, the test case generation algorithm and how the ME can be extended/adapted to include additional features.

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User Interface (UI) patterns are used extensively in the design of today's software. UI patterns embody commonly recurring solutions that solve common GUI design problems, such as "login," "file-open," and "search." Yet, testing of GUIs for functional correctness has largely ignored UI patterns. This paper formalizes the notion of a Pattern-Based Graphical User Interface (GUI) Testing method (PBGT) for systematizing and automating the GUI testing process. The space of all possible interactions with a GUI is typically very large. PBGT presents a new methodology to sample the input space using " UI Test Patterns," that embody commonly recurring solutions to test GUIs. Our empirical studies show that the PBGT methodology is effective in revealing faults in fielded GUIs.

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