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Framework for requirements-driven system design automation
Title
Framework for requirements-driven system design automation.
Creator
Fonoage, Mihai., Charles E. Schmidt College of Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description
In this thesis, a framework for improving model-driven system design productivity with Requirements-Driven Design Automation (RDDA) is presented. The key to the proposed approach is to close the semantic gap between requirements, components and architecture by using compatible semantic models for describing product requirements and component capabilities, including constraints. An ontology-based representation language is designed that spans requirements for the application domain, the...
Show moreIn this thesis, a framework for improving model-driven system design productivity with Requirements-Driven Design Automation (RDDA) is presented. The key to the proposed approach is to close the semantic gap between requirements, components and architecture by using compatible semantic models for describing product requirements and component capabilities, including constraints. An ontology-based representation language is designed that spans requirements for the application domain, the software design domain and the component domain. Design automation is supported for architecture development by machine-based mapping of desired product/subsystem features and capabilities to library components and by synthesis and maintenance of Systems Modeling Language (SysML) design structure diagrams. The RDDA framework uses standards-based semantic web technologies and can be integrated with exiting modeling tools. Requirements specification is a major component of the system development cycle. Mistakes and omissions in requirements documents lead to ambiguous or wrong interpretation by engineers, causing errors that trickle down in design and implementation with consequences on the overall development cost. We describe a methodology for requirements specification that aims to alleviate the above issues and that produces models for functional requirements that can be automatically validated for completeness and consistency. The RDDA framework uses an ontology-based language for semantic description of functional product requirements, SysML structure diagrams, component constraints, and Quality of Service. The front-end method for requirements specification is the SysML editor in Rhapsody. A requirements model in Web Ontology Language (OWL) is converted from SysML to Extensible Markup Language Metadata Interchange (XMI) representation., The specification is validated for completeness and consistency with a ruled-based system implemented in Prolog. With our methodology, omission s and several types of consistency errors present in the requirements specification are detected early on, before the design stage. Component selection and design automation have the potential to play a major role in reducing the system development time and cost caused by the rapid change in technology advances and the large solution search space. In our work, we start from a structured representation of requirements and components using SysML, and based on specific set of rules written in Prolog, we partially automate the process of architecture design.
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Date Issued
2010
PURL
http://purl.flvc.org/FAU/2975246
Subject Headings
Computer architecture, Computer software, Development, User-centered system design, Information technology, Management, Semantic Web
Format
Document (PDF)
Racial Inequalities in America: Examining Socieoeconomic Statistics Using the Semantic Web
Title
Racial Inequalities in America: Examining Socieoeconomic Statistics Using the Semantic Web.
Creator
Terrell, David J, Shankar, Ravi, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description
The visualization of recent episodes regarding apparently unjustifiable deaths of minorities, caused by police and federal law enforcement agencies, has been amplified through today's social media and television networks. Such events may seem to imply that issues concerning racial inequalities in America are getting worse. However, we do not know whether such indications are factual; whether this is a recent phenomenon, whether racial inequality is escalating relative to earlier decades, or...
Show moreThe visualization of recent episodes regarding apparently unjustifiable deaths of minorities, caused by police and federal law enforcement agencies, has been amplified through today's social media and television networks. Such events may seem to imply that issues concerning racial inequalities in America are getting worse. However, we do not know whether such indications are factual; whether this is a recent phenomenon, whether racial inequality is escalating relative to earlier decades, or whether it is better in certain regions of the nation compared to others. We have built a semantic engine for the purpose of querying statistics on various metropolitan areas, based on a database of individual deaths. Separately, we have built a database of demographic data on poverty, income, education attainment, and crime statistics for the top 25 most populous metropolitan areas. These data will ultimately be combined with government data to evaluate this hyp othesis, and provide a tool for predictive analytics. In this thesis, we will provide preliminary results in that direction. The methodology in our research consisted of multiple steps. We initially described our requirements and drew data from numerous datasets, which contained information on the 23 highest populated Metropolitan Statistical Areas in the United States. After all of the required data was obtained we decomposed the Metropolitan Statistical Area records into domain components and created an Ontology/Taxonomy via Protege to determine an hierarchy level of nouns towards identifying significant keywords throughout the datasets to use as search queries. Next, we used a Semantic Web implementation accompanied with Python programming language, and FuXi to build and instantiate a vocabulary. The Ontology was then parsed for the entered search query and returned corresponding results providing a semantically organized a nd relevant output in RDF/XML format.
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Date Issued
2015
PURL
http://purl.flvc.org/fau/fd/FA00004550, http://purl.flvc.org/fau/fd/FA00004550
Subject Headings
Data mining, Education -- Demographic aspects -- United States -- Statistics, Minorities -- United States -- Social conditions, Minorities -- United States -- Statistics, Race -- United States -- Statistics, Semantic Web, United States -- Ethnic relations -- Statistics, United States -- Race relations -- Statistics
Format
Document (PDF)