An Approach to Declaring Data Types for Formal Specifications

2014 ◽  
pp. 135-153 ◽  
Author(s):  
Xi Wang ◽  
Shaoying Liu
Keyword(s):  
Formal Specifications ◽  
Data Types

TFL: an algebraic language to specify the dynamic behaviour of knowledge-based systems

1996 ◽  
Vol 11 (3) ◽  
pp. 253-280 ◽  
Author(s):  
Christine Pierret-Golbreich ◽  
Xavier Talon
Keyword(s):  
Problem Solving ◽  
Formal Language ◽  
Dynamic Behaviour ◽  
Formal Specifications ◽  
Knowledge Based Systems ◽  
Strategic Knowledge ◽  
Data Types ◽  
Strategic Reasoning ◽  
Knowledge Based ◽  
Algebraic Data Types

AbstractTFL, the Task Formal Language, has been developed for integrating the static and dynamic aspects of knowledge based systems. This paper focuses on the formal specification of dynamic behaviour. Although fundamental in knowledge based systems, strategic reasoning has been rather neglected until now by the existing formal specifications. Most languages were generally more focused on the domain and problem-solving knowledge specification than on the control. The formalisation presented here differs from previous ones in several aspects. First, a different representation of dynamic knowledge is proposed: TFL is based on Algebraic Data Types, as opposed to dynamic or temporal logic. Second, dynamic strategic reasoning is emphasised, whereas existing languages only offer to specify algorithmic control. Then, TFL does not only provide the specification of the problem-solving knowledge of the object system, but also of its strategic knowledge. Finally, the dynamic knowledge of the meta-system itself is also specified. Moreover, modularisation is another important feature of the presented language.

scholarly journals Evaluation of clinical information modeling tools

2016 ◽  
Vol 23 (6) ◽  
pp. 1127-1135 ◽  
Author(s):  
Alberto Moreno-Conde ◽  
Tony Austin ◽  
Jesús Moreno-Conde ◽  
Carlos L Parra-Calderón ◽  
Dipak Kalra
Keyword(s):  
Clinical Information ◽  
Information Modeling ◽  
Evaluation Metrics ◽  
Tool Support ◽  
Formal Specifications ◽  
Functional Requirements ◽  
Data Types ◽  
Modeling Tools ◽  
Information Models ◽  
Toma De Decisiones

Abstract Objective Clinical information models are formal specifications for representing the structure and semantics of the clinical content within electronic health record systems. This research aims to define, test, and validate evaluation metrics for software tools designed to support the processes associated with the definition, management, and implementation of these models. Methodology The proposed framework builds on previous research that focused on obtaining agreement on the essential requirements in this area. A set of 50 conformance criteria were defined based on the 20 functional requirements agreed by that consensus and applied to evaluate the currently available tools. Results Of the 11 initiative developing tools for clinical information modeling identified, 9 were evaluated according to their performance on the evaluation metrics. Results show that functionalities related to management of data types, specifications, metadata, and terminology or ontology bindings have a good level of adoption. Improvements can be made in other areas focused on information modeling and associated processes. Other criteria related to displaying semantic relationships between concepts and communication with terminology servers had low levels of adoption. Conclusions The proposed evaluation metrics were successfully tested and validated against a representative sample of existing tools. The results identify the need to improve tool support for information modeling and software development processes, especially in those areas related to governance, clinician involvement, and optimizing the technical validation of testing processes. This research confirmed the potential of these evaluation metrics to support decision makers in identifying the most appropriate tool for their organization. OBJECTIVO Los Modelos de Información Clínica son especificaciones para representar la estructura y características semánticas del contenido clínico en los sistemas de Historia Clínica Electrónica. Esta investigación define, prueba y valida un marco para la evaluación de herramientas informáticas diseñadas para dar soporte en la en los procesos de definición, gestión e implementación de estos modelos. METODOLOGIA El marco de evaluación propuesto se basa en una investigación previa para obtener consenso en la definición de requisitos esenciales en esta área. A partir de los 20 requisitos funcionales acordados, un conjunto de 50 criterios de conformidad fueron definidos y aplicados en la evaluación de las herramientas existentes. RESULTADOS Un total de 9 de las 11 iniciativas identificadas desarrollando herramientas para el modelado de información clínica fueron evaluadas. Los resultados muestran que las funcionalidades relacionadas con la gestión de tipos de datos, especificaciones, metadatos y mapeo con terminologías u ontologías tienen un buen nivel de adopción. Se identifican posibles mejoras en áreas relacionadas con los procesos de modelado de información. Otros criterios relacionados con presentar las relaciones semánticas entre conceptos y la comunicación con servidores de terminología tienen un bajo nivel de adopción. CONCLUSIONES El marco de evaluación propuesto fue probado y validado satisfactoriamente contra un conjunto representativo de las herramientas existentes. Los resultados identifican la necesidad de mejorar el soporte de herramientas a los procesos de modelado de información y desarrollo de software, especialmente en las áreas relacionadas con gobernanza, participación de profesionales clínicos y la optimización de la validación técnica en los procesos de pruebas técnicas. Esta investigación ha confirmado el potencial de este marco de evaluación para dar soporte a los usuarios en la toma de decisiones sobre que herramienta es más apropiadas para su organización.

scholarly journals A Formal Approach to the Teaching of Abstract Data Types

10.28945/2477 ◽  
2002 ◽  
Author(s):  
Laura Felice ◽  
Liliana Martinez ◽  
Claudia Pereira
Keyword(s):  
Efficient Algorithm ◽  
Buenos Aires ◽  
System Engineering ◽  
Formal Specifications ◽  
Abstract Data Types ◽  
Data Types ◽  
Formal Approach ◽  
C Language ◽  
Abstract Data ◽  
Engineering Career

In this paper we present a methodology for the teaching of programming applied to an elementary course of the System Engineering career at the Universidad Nacional del Centro de la Provincia de Buenos Aires. This methodology starts with the formal specifications of abstract data types and concludes with an implementation of an efficient algorithm in C++ language. We describe the methodology, and a case of study showing the proposed methodology.

Integrating Visual and Bayesian Statistical Analyses in Single Case Experimental Research to Evaluate the Effectiveness and Magnitude of a Comprehensive Behavioral Intervention

2018 ◽  
Author(s):  
Prathiba Natesan ◽  
Smita Mehta
Keyword(s):  
Behavioral Intervention ◽  
Effect Size ◽  
Rate Ratio ◽  
Visual Analysis ◽  
Single Case ◽  
Small Sample ◽  
Statistical Analyses ◽  
Data Types ◽  
Ratio Effect ◽  
Small Sample Sizes

Single case experimental designs (SCEDs) have become an indispensable methodology where randomized control trials may be impossible or even inappropriate. However, the nature of SCED data presents challenges for both visual and statistical analyses. Small sample sizes, autocorrelations, data types, and design types render many parametric statistical analyses and maximum likelihood approaches ineffective. The presence of autocorrelation decreases interrater reliability in visual analysis. The purpose of the present study is to demonstrate a newly developed model called the Bayesian unknown change-point (BUCP) model which overcomes all the above-mentioned data analytic challenges. This is the first study to formulate and demonstrate rate ratio effect size for autocorrelated data, which has remained an open question in SCED research until now. This expository study also compares and contrasts the results from BUCP model with visual analysis, and rate ratio effect size with nonoverlap of all pairs (NAP) effect size. Data from a comprehensive behavioral intervention are used for the demonstration.

Sign in / Sign up

Export Citation Format

Share Document