Ontology Development for Bugtracking Information System

Ontology Development for Bugtracking Information System

Sumit Kumar Mishra

Assistant Professor,

Babu Banarasi Das Northern Indian Institute of Technology,

Lucknow, UP,

Dr. V. K. Singh

Professor. & Head – I.T.,

Babu Banarasi Das National Institute of Technology & Management,

Lucknow. India

Abstract – Ontology Development For Bug tracking Information System makes use of the semantic web and it used for valid bug information retrieve from the software company which help for software company in web based projects and other information like handling bugs, tracking old issues in software, searching for bug history in previous software.

Keyword – RDF, SPARQL,OWL, Web Semantic

1. INTRODUCTION

   Software company develops many web based software projects . A Bug Tracking information system detect the bug in software projects and give the proper solution for resolving these bug. In Ontology development for Bug tracking Information System we develop Bug tracking ontology and apply this ontology for information retrieval mechanism as a knowledge base for retrieving and managing acquaintance in a field of Software.[1,15]

   1.1 Proposed System

   The Proposed System consists of the Bug Tracking ontology. The Bug Tracking Ontology is built in Protégé

   1. This ontology provides for the framework of the Bug tracking ontology System. DotNetRDF which is a RDF API used in Microsoft Visual Studio for implementing Semantic Web Solution is extensively exploited over here. A SPARQL query is submitted to the DotNetRDF API which in conjunction with ASP.NET provides results as queried by the SPARQL interface. So the request and response is handled by the system.[15]

      Fig.1. Bug Tracking information system Model

      1. BUG TRACKER ONTOLOGY DESIGN

         Bug tracker ontology is based on Web based project which consists Bug_Classes that is related directly Bug_information system. According to formal definition ontology consists 4 tuples <C,I,R,A> to design basic ontology we define all tuples.[4,5]

         • Class(C)

         • Instances (I)

         • Relationship(R)

         • Axioms(A)

   1. Classes and properties of Bug Tracking Ontology

   A class provides an abstraction mechanism for grouping data members with same type characteristics [6], whilst a property is often used to identify the non hierarchical relationships between domain and range (denoted as ). Web Ontology language(OWL) provides two types of properties: data property and object property. Data property is define attribute or data items while object property is a binary relationship between two classes. Bug ontology define relationship between super class and subclass and Things represent the super class Bug tracking information system.

   Fig.2 User Login System

   Fig.3 Class hierarchy Bug Tracking Information system

   1. BUG PROJECT SYSTEM

      With the help of this information system we submit new bug in Bug Database and set its priority on the basis of complexity of software. Also we add the part of the program where bug found.

      Fig.4. Bug Submit File

   2. SPARQL Query for related to Bug Ontology PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-

      syntax-ns#>

      PREFIX owl:

      <http://www.w3.org/2002/07/owl#>

      PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>

      PREFIX rdfs:

      <http://www.w3.org/2000/01/rdf-schema#>

      SELECT *

      where {

      ?element

      <http://www.semanticweb.org/rs/ontologies/2014/9/Bug- 25#hasBugName> ?BUG_NAME.

      ?element

      <http://www.semanticweb.org/rs/ontologies/2014/9/Bug- 25#hasBugID> ?Related_Bug_ID.

      { SELECT ?Related_Bug_ID where

      {

      ?element<http://www.semanticweb.org/rs/ontologies/2014/ 9/Bug-25#hasRelatedBug_ID> ?Related_Bug_ID.

      ?element<http://www.semanticweb.org/rs/ontologies/2014/ 9/Bug-25#hasBugPriority>

      <http://www.semanticweb.org/rs/ontologies/2014/9/Bug- 25#3>.

      }

      }

      }

   3. RDF(Resource description Framework) FILE FOR BUG TRACKING INFORMATION SYSTEM

      <?xml version="1.0" encoding="utf-8"?>

      <!DOCTYPE rdf:RDF [

      <!ENTITY rdf 'http://www.w3.org/1999/02/22- rdf-syntax-ns#'>

      <!ENTITY rdfs 'http://www.w3.org/2000/01/rdf- schema#'>

      <!ENTITY xsd

      'http://www.w3.org/2001/XMLSchema#'>

      ]>

      <rdf:RDF xmlns:rdfs="http://www.w3.org/2000/01/rdf- schema#" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax- ns#">

      <rdf:Description rdf:about="http://www.semanticweb.org/dell/ontologies/20 15/0/untitled_ontology-6#EmployeeIdafa14055-6a5a-45f2- b2343-7cd5f3ca64">

      <ns0:Bugsearch xmlns:ns0="http://www.semanticweb.org/dell/ontologies/2 015/0/untitled_ontology-6#">BugName</ns0: Bugsearch >

      <ns1: Projectinformation xmlns:ns1="http://www.semanticweb.org/dell/ontologies/2 015/0/untitled_ontology-6#">Webbased</ns1: Projectinformation >

      <ns2:Registraion xmlns:ns2="http://www.semanticweb.org/dell/ontologies/2 015/0/untitled_ontology-6#">redWheat</ns2: Registraion

      >

      </rdf:Description>

      </rdf:RDF>

   4. WORKING OF SOFTWARE

      This interface provide a basic searching features .with the help of Bug tracking information system we search any bug which is affected to running mode project in software company we can resolve easily. This interface based on semantic web concept so extracting the information is done very rapidly. In project development time if developer found new bug than this interface provide a basic feature submitting new bug concept. With the help of this concept developer add new bug in bug tracking ontology based information system. This interface look like a search engine also that involves semantic web concept you can find bug information on similar matters by searching through.

   5. CONCLUSION AND FUTURE SCOPE

      The future scope of our work is to apply the potential of Knowledge Representation[12,13,14] along with reasoning in the Web context. The use of semantic web in Bug tracking Information System helps the machine to take the appropriate decision regarding software.

      Fig.5. Bug Tracking Information System Ontology

   6. REFERENCES

1. Sumit Kumar mishra, Dr. V.K. Singh Anurag TiwariOntology development for agriculture research a case study of wheat journal of basic and applied engineering research.

2. Six Basic Classes of Wheat Minnesota Association of Wheat Growers.

3. Chalkley , D,(2010), Invasive Fungi: Alternaria leaf blight of Wheat Alternaria triticina. Systematic mycology and Microbiology laboratory , Agricultural Research Service. Unfitted States Department Of Agriculture Archived From the original on 29 October 2014.

4. Natalya F. Noy and Deborah L. McGuinness, Ontology Development 101: A Guide for Creating Your First Ontology.

5. Toby Segaran, Colin Evans, and Jamie Taylor,

   Programming the Semantic Web.

6. Gómez-Pérez, A., Fernández-López, M., Corcho, O. Ontological Engineering, with examples from the areas of Knowledge Management, e-Commerce and the Semantic Web. Springer, London, Berlin (2003)

7. Opijnen, Marc van, The European Legal Semantic Web: Completed Building Blocks nd Future Work (November 22, 2012). European Legal Access Conference, November 2012.

8. Amit Sheth,Cartic Ramakrishnan, and Christopher Thomas, 'Semantics for The Semantic Web: the Implicit, the Formal and the Powerful',International Journal on Semantic Web & Information Systems, 1 (no. 1), 2005, pp. 1-18.

9. 3. Brachman , R.J., McGuinness, D.L., Patel-Schneider, P.F., Resnick, L.A. and Borgida, A. (1991). Living with CLASSIC: When and how to use KL-ONE-like language. Principles of Semantic Networks. J. F. Sowa, editor, Morgan Kaufmann: 401-456

10. Legal Semantic Web- A Recommendation System gaurav kant, Gaurav Kant, V.K.Singh, M. Darbari, D.

    Yagyasen4,P.K. Shukla International journal ICANI

11. Bob DuCharme, Learning SPARQL, OREILLY,2011.

12. Gómez-Pérez, A., Fernández-López, M., Corcho, O. Ontological Engineering, with examples from the areas of Knowledge Management, e-Commerce and the Semantic Web. Springer, London, Berlin (2003)

13. D Yagyasen, M Darbari, P K Shukla, V K Singh,(2013). Diversity and Convergence Issues in Evolutionary Multi- objective Optimization: Application to Agriculture Science, IERI Procedia, Elsevier.

14. D Yagyasen, M Darbari, H Ahmed, (2013). Transforming Non-Living to Living: A Case on Changing Business Environment, 2013, IERI Procedia, Elsevier.

15. S.k.mishra Dr.V.K. Singh Gaurav Kant Ontology development for Wheat Information System IJERT.

About Authors

1. SUMIT KUMAR MISHRA received his B.Tech degree from U.P.T.U. in 2013. Currently he is Assistant Professor, Babu Banarasi Das Northern Indian Institute of Technology, Lucknow Uttar Pradesh, India.

2. Dr. V.K. SINGH Prof. & Head – I.T., Babu Banarasi Das National Institute of Technology & Management,Lucknow. India.