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Guaraná domain‐specific language is aimed to design enterprise application integration models. Although the language has been broadly used in the industry and academy, the design of its graphical notation was based in the common sense and social opinion of its developers rather than theoretical principles and empirical evidence. Thus, Guaraná becomes as an option for studying, modifying, and improving its concrete syntax. In this article we conducted an experiment with 85 participants in order to evaluate the semantic transparency of the concrete syntax of Guaraná. The study concludes that the language is not found to be semantically immediate because most of the language constructs used in the graphical notation of Guaraná are not semantically immediate, that is, a novice reader is not able to infer their meaning from their appearance alone. [ABSTRACT FROM AUTHOR]

Implementation of the coalescent model in a Bayesian framework is an emerging strength in genetically based species delimitation studies. By providing an objective measure of species diagnosis, these methods represent a quantitative enhancement to the analysis of multilocus data, and complement more traditional methods based on phenotypic and ecological characteristics. Recognized as two species 20 years ago, mouse lemurs (genus Microcebus) now comprise more than 20 species, largely diagnosed from mt DNA sequence data. With each new species description, enthusiasm has been tempered with scientific scepticism. Here, we present a statistically justified and unbiased Bayesian approach towards mouse lemur species delimitation. We perform validation tests using multilocus sequence data and two methodologies: (i) reverse-jump Markov chain Monte Carlo sampling to assess the likelihood of different models defined a priori by a guide tree, and (ii) a Bayes factor delimitation test that compares different species-tree models without a guide tree. We assess the sensitivity of these methods using randomized individual assignments, which has been used in bpp studies, but not with Bayes factor delimitation tests. Our results validate previously diagnosed taxa, as well as new species hypotheses, resulting in support for three new mouse lemur species. As the challenge of multiple researchers using differing criteria to describe diversity is not unique to Microcebus, the methods used here have significant potential for clarifying diversity in other taxonomic groups. We echo previous studies in advocating that multiple lines of evidence, including use of the coalescent model, should be trusted to delimit new species. [ABSTRACT FROM AUTHOR]