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Models in Software Engineering

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TLDR
This research work proposes automated knowledge acquisition to support language engineers in early language development phases with an iterative approach in which DSL development benefits from formalized knowledge sources and information extraction from text supporting domain analysis and metamodel construction.
Abstract
In model-driven engineering, domain-specific languages (DSLs) play an important role in providing well-defined environments for modeling different aspects of a system. Detailed knowledge of the application domain as well as expertise in language engineering is required to create new languages. This research work proposes automated knowledge acquisition to support language engineers in early language development phases. We describe an iterative approach in which DSL development benefits from formalized knowledge sources and information extraction from text supporting domain analysis and metamodel construction. We show how the acquired knowledge is used to guide language engineers and how knowledge acquisition is adapted according to modeling decisions.

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Citations
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Systematic literature review of the objectives, techniques, kinds, and architectures of models at runtime

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Architecture Fault Modeling with the AADL Error-Model Annex

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References
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The magical number seven, plus or minus two: some limits on our capacity for processing information

TL;DR: The theory of information as discussed by the authors provides a yardstick for calibrating our stimulus materials and for measuring the performance of our subjects and provides a quantitative way of getting at some of these questions.
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Cognitive load during problem solving: Effects on learning

TL;DR: It is suggested that a major reason for the ineffectiveness of problem solving as a learning device, is that the cognitive processes required by the two activities overlap insufficiently, and that conventional problem solving in the form of means-ends analysis requires a relatively large amount of cognitive processing capacity which is consequently unavailable for schema acquisition.
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Cognitive Load Measurement as a Means to Advance Cognitive Load Theory

TL;DR: In this paper, the authors discuss cognitive load measurement techniques with regard to their contribution to cognitive load theory (CLT), which is concerned with the design of instructional methods that efficiently use people's limited cognitive processing capacity to apply acquired knowledge and skills to new situations (i.e., transfer).