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Ontology classification for semantic-web-based software engineering


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  • 1.
    • Ontology Classification for Semantic-Web-Based Software Engineering
    • DECEMBER 2009
  • 2. 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.... Please to keep provide many eBooks and technology news for FREE. Encourage us by Clicking on the advertisement in these Blog.
  • 3. 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
  • 4. 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
  • 5. 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
  • 6. 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.
  • 7. 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
  • 8. 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.
  • 9. 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.
  • 10. 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
  • 11. 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.
  • 12. 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
  • 13. 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
  • 14. 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
  • 15. 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
  • 16. 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
  • 17. 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
  • 18. 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.
  • 19. 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.
  • 20.
    • Queries
  • 21.
    • Thank you