Automatic Generation of Students’ Conceptual Models from Answers in Plain Text

2007 ◽  
pp. 329-333 ◽  
Author(s):  
D. Pérez-Marín ◽  
E. Alfonseca ◽  
P. Rodríguez ◽  
I. Pascual-Nieto
Keyword(s):  
Conceptual Models ◽  
Automatic Generation ◽  
Plain Text

Automatic Generation of ETL Physical Systems from BPMN Conceptual Models

2015 ◽  
pp. 239-247 ◽  
Author(s):  
Orlando Belo ◽  
Claudia Gomes ◽  
Bruno Oliveira ◽  
Ricardo Marques ◽  
Vasco Santos
Keyword(s):  
Conceptual Models ◽  
Automatic Generation ◽  
Physical Systems

scholarly journals Automatic Generation of Test Cases from UML Models

2018 ◽  
Vol 21 (1) ◽  
Author(s):  
Constanza Pérez ◽  
Beatriz Marín
Keyword(s):  
Conceptual Models ◽  
State Transition ◽  
Automatic Generation ◽  
Test Cases ◽  
Design And Implementation ◽  
Model Based ◽  
Model Based Testing ◽  
The Cost ◽  
Early Phases ◽  
Uml Models

[Context] The growing demand for high-quality software has caused the industry to incorporate processes to enable them to comply with these standards, but increasing the cost of development. A strategy to reduce this cost is to incorporate quality evaluations from early stages of software development. A technique that facilitates this evaluation is the model-based testing, which allows to generate test cases at early phases using as input the conceptual models of the system. [Objective] In this paper, we introduce TCGen, a tool that enables the automatic generation of abstract test cases starting from UML conceptual models. [Method] The design and implementation of TCGen, a technique that applies different testing criteria to class diagrams and state transition diagrams to generates test cases, is presented as a model-based testing approach. To do that, TCGen uses UML models, which are widely used at industry and a set of algorithms that recognize the concepts in the models in order to generate abstract test cases. [Results] An exploratory experimental evaluation has been performed to compare the TCGen tool with traditional testing. [Conclusions] Even though the exploratory evaluation shows promising results, it is necessary to perform more empirical evaluations in order to generalize the results. Abstract (in Spanish): [Contexto] La creciente demanda de software de alta calidad ha provocado que la industria incorpore procesos para permitirles cumplir con estos estándares, pero aumentando el costo del desarrollo. Una estrategia para reducir este costo es incorporar evaluaciones de calidad desde las primeras etapas del desarrollo del software. Una técnica que facilita esta evaluación es la prueba basada en modelos, que permite generar casos de prueba en fases tempranas utilizando como entrada los modelos conceptuales del sistema. [Objetivo] En este artículo, presentamos TCGen, una herramienta que permite la generación automática de casos de pruebas abstractas a partir de modelos conceptuales UML. [Método] El diseño e implementación de TCGen, una técnica que aplica diferentes criterios de prueba a los diagramas de clases y diagramas de transición de estados para generar casos de prueba, se presenta como un enfoque de prueba basado en modelos. Para hacer eso, TCGen utiliza modelos UML, que son ampliamente utilizados en la industria y un conjunto de algoritmos que reconocen los conceptos en los modelos para generar casos de prueba abstractos. [Resultados] Se realizó una evaluación experimental exploratoria para comparar la herramienta TCGen con las pruebas tradicionales. [Conclusiones] Aunque la evaluación exploratoria muestra resultados prometedores, es necesario realizar más evaluaciones empíricas para generalizar los resultados.  

Conceptual models for automatic generation of knowledge-acquisition tools

1993 ◽  
Vol 8 (1) ◽  
pp. 27-47 ◽  
Author(s):  
Henrik Eriksson ◽  
Mark A. Musen
Keyword(s):  
Knowledge Acquisition ◽  
Domain Knowledge ◽  
Conceptual Models ◽  
Automatic Generation ◽  
Design Models ◽  
Domain Specific ◽  
Generic Design ◽  
Relevant Domain

AbstractInteractive knowledge-acquisition (KA) programs allow users to enter relevant domain knowledge according to a model predefined by the tool developers. KA tools are designed to provide conceptual models of the knowledge to their users. Many different classes of models are possible, resulting in different categories of tools. Whenever it is possible to describe KA tools according to explicit conceptual models, it is also possible to edit the models and to instantiate new KA tools automatically for specialized purposes. Several meta-tools that address this task have been implemented. Meta-tools provide developers of domain-specific KA tools with generic design models, or meta-views, of the emerging KA tools. The same KA tool can be specified according to several alternative meta-views.

The Role of Visual Distractors in the Simon Effect

2017 ◽  
Vol 64 (6) ◽  
pp. 387-397 ◽  
Author(s):  
Luisa Lugli ◽  
Stefania D’Ascenzo ◽  
Roberto Nicoletti ◽  
Carlo Umiltà
Keyword(s):  
Simon Effect ◽  
Simon Task ◽  
Automatic Generation ◽  
Spatial Code ◽  
Attentional Model ◽  
Previous Evidence ◽  
Spatial Stimulus ◽  
Attentional Resources ◽  
Code Changes

Abstract. The Simon effect lies on the automatic generation of a stimulus spatial code, which, however, is not relevant for performing the task. Results typically show faster performance when stimulus and response locations correspond, rather than when they do not. Considering reaction time distributions, two types of Simon effect have been individuated, which are thought to depend on different mechanisms: visuomotor activation versus cognitive translation of spatial codes. The present study aimed to investigate whether the presence of a distractor, which affects the allocation of attentional resources and, thus, the time needed to generate the spatial code, changes the nature of the Simon effect. In four experiments, we manipulated the presence and the characteristics of the distractor. Findings extend previous evidence regarding the distinction between visuomotor activation and cognitive translation of spatial stimulus codes in a Simon task. They are discussed with reference to the attentional model of the Simon effect.

Review of Depression in childhood: Diagnosis, treatment, and conceptual models.

1978 ◽  
Vol 23 (6) ◽  
pp. 472-472
Author(s):  
JAMES M. STEDMAN
Keyword(s):  
Conceptual Models
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