Further evidence for mixed emotions.

Emotion theorists have long debated whether valence, which ranges from pleasant to unpleasant states, is an irreducible aspect of the experience of emotion or whether positivity and negativity are separable in experience. If valence is irreducible, it follows that people cannot feel happy and sad at the same time. Conversely, if positivity and negativity are separable, people may be able to experience such mixed emotions. The authors tested several alternative interpretations for prior evidence that happiness and sadness can co-occur in bittersweet situations (i.e., those containing both pleasant and unpleasant aspects). One possibility is that subjects who reported mixed emotions merely vacillated between happiness and sadness. The authors tested this hypothesis in Studies 1–3 by asking subjects to complete online continuous measures of happiness and sadness. Subjects reported more simultaneously mixed emotions during a bittersweet film clip than during a control clip. Another possibility is that subjects in earlier studies reported mixed emotions only because they were explicitly asked whether they felt happy and sad. The authors tested this hypothesis in Studies 4–6 with open-ended measures of emotion. Subjects were more likely to report mixed emotions after the bittersweet clip than the control clip. Both patterns occurred even when subjects were told that they were not expected to report mixed emotions (Studies 2 and 5) and among subjects who did not previously believe that people could simultaneously feel happy and sad (Studies 3 and 6). These results provide further evidence that positivity and negativity are separable in experience. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Does Kripke’s Argument Against Functionalism Undermine the Standard View of What Computers Are?

Kripke’s argument against functionalism extended to physical computers poses a deep philosophical problem (not previously addressed in the literature) for understanding the standard view of what computers are. The problem puts into jeopardy the definition in the standard view that computers are physical machines for performing physical computations. Indeed, it is entirely possible that, unless this philosophical problem is resolved, we will never have a good understanding of computers and may never know just what they are.     

Efficient and scalable omniscient debugging for model transformations

This paper discusses a technique for supporting omniscient debugging for model transformations, which are used to define core operations on software and system models. Similar to software systems developed using general-purpose languages, model transformations are also subject to human error and may possess defects. Existing model-driven engineering tools provide stepwise execution to aid developers in locating and removing defects. In this paper, we describe our investigation into a technique and associated algorithms that support omniscient debugging features for model transformations. Omniscient debugging enables enhanced navigation and exploration features during a debugging session beyond those possible in a strictly stepwise execution environment. Finally, the execution time performance is comparatively evaluated against stepwise execution, and the scalability (in terms of memory usage) is empirically investigated.