No abstract

We describe the semantics of statecharts as implemented in the STATEMATE system. This was the first executable semantics defined for the language and has been in use for almost a decade. In terms of the controversy around whether changes made in a given step should take effect in the current step or in the next one, this semantics adopts the latter approach.

Abstract. While message sequence charts (MSCs) are widely used in industry to document the interworking of processes or objects, they are expressively weak, being based on the modest semantic notion of a partial ordering of events as defined, e.g., in the ITU standard. A highly expressive and rigorously defined MSC language is a must for serious, semantically meaningful tool support for use-cases and scenarios. It is also a prerequisite to addressing what we regard as one of the central problems in behavioral specification of systems: relating scenario-based inter-object specification to state-machine intra-object specification. This paper proposes an extension of MSCs, which we call live sequence charts (or LSCs), since our main extension deals with specifying "liveness", i.e., things that must occur. In fact, LSCs allow the distinction between possible and necessary behavior both globally, on the level of an entire chart and locally, when specifying events, conditions and progress over time within a chart. This makes it possible to specify forbidden scenarios, for example, and enables naturally specified structuring constructs such as subcharts, branching and iteration.

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The higraph, a general kind of diagramming object, forms a visual formalism of topological nature. Higraphs are suited for a wide array of applications to databases, knowledge representation, and, most notably, the behavioral specification of complex concurrent systems using the higraph-based language of statecharts.

No abstract

The paradigm of simulated annealing is applied to the problem of drawing graphs “nicely.” Our algorithm deals with general undirected graphs with straight-line edges, and employs several simple criteria for the aesthetic quality of the result. The algorithm is flexible, in that the relative weights of the criteria can be changed. For graphs of modest size it produces good results, competitive with those produced by other methods, notably, the “spring method” and its variants.

In studies of vision and audition, stimuli can be systematically varied by wavelength and frequency, respectively, but there is no equivalent metric for olfaction. Restricted odorant-feature metrics such as number of carbons and functional group do not account for response patterns to odorants varying along other structural dimensions. We generated a multidimensional odor metric, in which each odorant molecule was represented as a vector of 1,664 molecular descriptor values. Revisiting many studies, we found that this metric and a second optimized metric were always better at accounting for neural responses than the specific metric used in each study. These metrics were applicable across studies that differed in the animals studied, the type of olfactory neurons tested, the odorants applied and the recording methods used. We use this new metric to recommend sets of odorants that span the physicochemical space for use in olfaction experiments.