Ontology classification for semantic-web-based software engineering
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Ontology classification for semantic-web-based software engineering



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    Ontology classification for semantic-web-based software engineering Ontology classification for semantic-web-based software engineering Presentation Transcript

      • Ontology Classification for Semantic-Web-Based Software Engineering
      • DECEMBER 2009
    • By. P. Victer Paul Dear, We planned to share our eBooks and project/seminar contents for free to all needed friends like u.. To get to know about more free computerscience ebooks and technology advancements in computer science. Please visit.... http://free-computerscience-ebooks.blogspot.com/ http://recent-computer-technology.blogspot.com/ http://computertechnologiesebooks.blogspot.com/ Please to keep provide many eBooks and technology news for FREE. Encourage us by Clicking on the advertisement in these Blog.
    • About Authors
      • Yajing Zhao
        • Working toward the PhD degree at the University of Texas at Dallas.
        • Software architecture and design, service oriented architecture, semantic Web services.
      • Jing Dong, Senior Member, IEEE
        • PhD degrees in computer science from the University of Waterloo, Canada, in 2002.
        • Formal and automated methods for software engineering, software modeling and design, services computing, and visualization
      • Tu Peng
        • Working toward the PhD degree at the University of Texas at Dallas.
        • Formal modeling and verification of software design, security, services computing, and model checking
    • Aim
      • The Semantic Web provides a way to improve information sharing and reuse.
      • In Software Engineering, Information sharing and reuse have the following benefits:
        • improving productivity
        • shortening development life cycle
        • decreasing cost
        • increasing product quality
      • classifies the ontologies developed for software engineering and presents the benefits of their applications
    • Introduction
      • The Semantic Web which helps sharing and reusing data across application, enterprise, and community boundaries.
      • Ontology defines a set of representational primitives with which a domain of knowledge is modeled.
      • The W3C standards,
        • OWL
        • RDF
      • maintains information in the format that can be understood and processed by automated tools
    • Introduction
      • Software development is a complex process which produces a large amount of information.
      • Effort has been made to improve the software process like IDE,CASE.
      • Reusing existing information saves efforts. A method that facilitates information retrieval and promotes reuse is highly demanded.
      • Globalization need information sharing helps to prevent inconsistency.
    • Software Process Ontology
      • Each oval with solid border represents a concept, each directed line represents a relationship between two concepts, and the text on the line denotes the type of the relationship.
      • an oval with dashed lines represents an ontology, which can be seen as a meta concept.
      • Ontology 1. Software process ontology
    • Domain Ontologies
      • Domain engineering collects useful information within a specific domain, which can be maintained and reused in future application development in the same domain.
      • Reusing domain information may reduce time and save the effort of gathering information.
      • Ontology 2. Application domain ontology , which represents the knowledge of an application domain and the business information required for building software applications in a specific domain.
      • Ontology 3. Application domain feature model ontology , which models the features of software systems in the same application domain.
    • Requirement Ontology
      • Desired software characteristics specified by the customer
        • Functional Requirements (FRs)
          • sequence of actions under a particular context
        • Non-Functional Requirements (NFRs)
          • quality-related characteristics of a system.
      • Ontology 4. System behavior ontology , which models system behaviors.
      • The main concepts of this ontology include event, action, reservation, etc.
      • Relationships include making agreement, making reservation, etc.
    • Quality Ontologies
      • measured along the software attributes: capacity, usability, performance, reliability, installability, maintainability, availability, etc
      • Ontology 15. Quality ontology
      • Ontology 16. Testing ontology
      • Ontology 17. Defect ontology
    • Technology Ontology
      • built to act as a library, to provide engineers with possible information, and to help engineers to pick up the most appropriate tools or technologies
      • Ontology 18. Technology ontology , which is a repository of software development technologies (J2EE,.Net), environments, platforms, tools.
    • Other Ontologies
      • Architecture and Design Ontologies
        • Ontology 5. Software architecture ontology
        • Ontology 6. Application logic ontology
        • Ontology 7. Object-Oriented design ontology
      • Implementation Ontologies
        • Ontology 9. Software artifact ontology
        • Ontology 10. Object-oriented source code ontology
        • Ontology 11. Version ontology
        • Ontology 12. System configuration ontology
      • Documentation Ontologies
        • Ontology 13. Documentation ontology
        • Ontology 14. Document ontology
    • Semantic Web Applications In Software Engineering
      • how these ontologies and the Semantic Web technologies are used to improve software engineering.
      • problems from two perspective in software engineering,
        • The life-cycle perspective
          • problem exist in a particular software engineering phase
        • The critical issue perspective
          • problem exist throughout the entire life
      • introduces problems from these perspectives and discusses how they can be improved by using the Semantic Web technologies
    • From Life-Cycle Perspective
        • Requirement Engineering Phase
          • Application domain ontology and quality ontology
        • Software Design Phase
          • Application domain feature model ontology and Pattern ontology
        • Implementation and Integration Phase
          • Application domain ontology and testing ontology
        • Software Testing Phase
          • Software testing ontology
        • Software Maintenance Phase
          • Software maintenance ontology
    • Usage of Ontologies to Support Engineering Phases
        • ‘ x’ indicates that the ontology has been used by some researcher work to solve problems.
        • ‘ ?’ indicates that the ontology can be used to solve the problem but there is no work on it yet
    • From Critical Issues Perspective
      • Documentation
        • software artifact ontology and application domain ontology
      • Traceability
        • object-oriented source code ontology and documentation ontology
      • Change Control
        • domain ontology, pattern and version ontology
      • Quality Control
        • object-oriented source code ontology, defect ontology, and version ontology
      • Reuse
        • software artifact ontology and the domain ontology
    • Benefits of Ontologies to Critical Issues
        • ‘ x’ indicates that the ontology has been used by some researcher work to solve problems.
        • ‘ ?’ indicates that the ontology can be used to solve the problem but there is no work on it yet
    • Conclusion
      • many discussions and suggestions about improving software engineering process by using ontology and the Semantic Web techniques.
      • To the best of our knowledge, there is no classification or assessment on these approaches yet.
      • Our goal in this paper is to provide a review on current status of this field.
    • References
      • A.P. Ambro´ sio, D.C. de Santos, F.N. de Lucena, and J.C. de Silva, “Software Engineering Documentation: An Ontology-Based Approach,” Proc. Web Media and LA-Web Joint Conf. 10th Brazilian Symp. Multimedia and the Web Second Latin Am. Web Congress, pp. 38-40, 2004.
      • A. April, J.-M. Desharnais, and R. Dumke, “A Formalism of Ontology to Support a Software Maintenance Knowledge-Based System,” Proc. 18th Int’l Conf. Software Eng. and Knowledge Eng., 2006.
      • Queries
      • Thank you