Ontology classification for semantic-web-based software engineering

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  • 1.
    • Ontology Classification for Semantic-Web-Based Software Engineering
    • IEEE TRANSACTIONS ON SERVICES COMPUTING,
    • 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.... 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.
  • 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