Google scholar arxiv informatics ads IJAIS publications are indexed with Google Scholar, NASA ADS, Informatics et. al.

Call for Paper

-

July Edition 2021

International Journal of Applied Information Systems solicits high quality original research papers for the July 2021 Edition of the journal. The last date of research paper submission is June 15, 2021.

Coalescence of Evolutionary Multi-Objective Decision Making approach and Genetic Programming for Selection of Software Quality Parameter

Manuj Darbari, Himanshu Pandey, V. K Singh, Gaurav Kumar Srivastava Published in Software Engineering

International Journal of Applied Information Systems
Year of Publication: 2014
© 2013 by IJAIS Journal
10.5120/ijais14-451255
Download full text
  1. Manuj Darbari, Himanshu Pandey, V k Singh and Gaurav Kumar Srivastava. Article: Coalescence of Evolutionary Multi-Objective Decision Making approach and Genetic Programming for Selection of Software Quality Parameter. International Journal of Applied Information Systems 7(11):18-22, November 2014. BibTeX

    @article{key:article,
    	author = "Manuj Darbari and Himanshu Pandey and V.k Singh and Gaurav Kumar Srivastava",
    	title = "Article: Coalescence of Evolutionary Multi-Objective Decision Making approach and Genetic Programming for Selection of Software Quality Parameter",
    	journal = "International Journal of Applied Information Systems",
    	year = 2014,
    	volume = 7,
    	number = 11,
    	pages = "18-22",
    	month = "November",
    	note = "Published by Foundation of Computer Science, New York, USA"
    }
    

Abstract

Selection of quality parameters for software according to customer expectation is a complex task which can be prospected as a constrained multi-objective optimization and a multiple criteria decision making problem. For a Software Quality: Usability, Reliability, Complexity, Capability, Durability, Maintainability are the major factors affecting its performance. We proffer a concept of a Multi-Objective Decision making approach using Genetic Programming to appraising the Software Quality Parameters. The paper highlights estimating the Quality Parameters of Software using Multi objective Decision Making approaches and Genetic Programming. The outcome of a Multi objective fed into Genetic Programming for further mutation, to find out the perfect combination of variables of these quantities. The above work is substantiating an optimum trade-off needs to be reached in the formation of good software.

Reference

  1. Hashem, M. M. A: 1999 "Global Optimization Through a new class of Evolutionary Algorithms", PhD Dissertation, Saga University, Japan.
  2. H RuotsalaIinen: January 2010. "Interactive Multiobjective Optimization in Model-based Decision Making with Applications".
  3. S. RIOS-INSUA, J. G PACHON, A. MATEOS 1994: "A Method Of Multiobjective Decision Making Using a Vector Value Function".
  4. M Srivastava, H Pandey, S Shukla, B. K Thakur, "A Literature Review of E- Learning Model Based on Semantic Web Technology", International Journal of Scientific & Engineering Research, Volume 5, Issue 10, October -2014.
  5. J Verma, S Bansal, H Pandey, "Develop Framework for Selecting Best Software Development Methodology", International Journal of Scientific & Engineering Research, Volume 5, Issue 4, April -2014.
  6. Yonghua Zhou Yuliu Chen, "The QFD-based Decision-making Approach for Strategic BPR" Beijing 100084, P. R. China.
  7. TIAN Na, CHE A-da, August 20-22, 2007 "Goal Programming in Quality Function Deployment Using Genetic Algorithm", International Conference on Management Science & Engineering (14th).
  8. K. Y. Chan1, T. S. Dillon1, C. K. Kwong2 and S. H. Ling," Using Genetic Programming for Developing Relationship between Engineering Characteristics and Customer Requirements in New Products" 1Digital Ecosystems and Business Intelligence Institute, Curtin University of Technology, Perth, Australia.
  9. Qi Wang, Jie Zhu, Bo Yu, 2007 "Feature Selection and Clustering in Software Quality Prediction", Evaluation and Assessment in Software Engineering.
  10. L Murphy, H S. Abdel-Aty-Zohd, M. Hashem-Sherif, 2005 "A Genetic Algorithm Tracking Model For Product Deployment in Telecom Services" ,0-7803-9197-7/05/© IEEE.
  11. S K Dubey, S Ghosh, A Rana ,"Comparison of Software Quality Models: An Analytical Approach", ISSN 2250-2459, Volume 2, Issue 2, February 2012.
  12. Yi. Liu, TaghiM. Khoshgoftaar , "Genetic Programming Model for Software Quality Classification", 6th IEEE International Symposium on High Assurance Systems Engineering (HASE'01) 2001.
  13. S Keshavarz and R. Javidan, August 2011 "Software Quality Control Based on Genetic Algorithm", Vol. 3, No. 4,.
  14. S Bouktif, Bal´azsK´egl, H. Sahraoui, "Combining Software Quality Predictive Models: An Evolutionary Approach", Dept. of Computer Science and Op. Res. , University of Montreal C. P. 6128 Succ. Centre-Ville, Canada.
  15. H. Kargupta, , 1996 "The Gene Expression Messy Genetic Algorithm", published in IEEE conference on Evolutionary Computation, Nagoya, Japan.
  16. K. Arai, Vol. 1, No. 8, 2012 "Clustering Method Based on Messy Genetic Algorithm: GA for Remote Sensing Satellite Image Classifications", International Journal of Advanced Research in Artificial Intelligence.
  17. R. Sobiesiak and Tim, "Complexity analysis: a quantitative approach to usability engineering", IBM Rochester Laboratory.
  18. M Darbari, N Dhanda "Applying Constraints in Model Driven Knowledge Representation Framework. ", International Journal of Hybrid Information Technology 3 (3), 4, 2010.
  19. M Darbari, S Medhavi, AK Srivastava "Development of effective Urban Road Traffic Management using workflow techniques" for upcoming metro cities like Lucknow (India),Development 2 (2)4,2008.
  20. IA Siddiqui, M Darbari: "Application of Use Case for Identification of Root Cause of the Dependencies and Mutual Understanding and Cooperation Difficulties in Software Systems", International Journal of Applied Software Engineering, 4, 10-20.
  21. IA Siddiqui, M Darbari, S Bansal, "Application of Activity Theory and Particle Swarm Optimization Technique in Cooperative Software Development", International Review on Computers & Software 7 (5)
  22. IA Siddiqui, M Darbari, "A Group Awareness and collaboration in Distributed Software Development", International Journal of Scientific & Engineering Research Volume 3, Issue 3, March -2012.
  23. N EijiNawa and T Furuhashi, "Fuzzy system Parameters: Discovery by bacterial Evolutionary Algorithm", IEEE Transaction on Fuzzy system. Volume 7, No 5, 1991.
  24. A Gonzalez and F Hemera , "Multi- stage Genetic fuzzy systems based on the Iterative Rule Learning Approach ", Math ware & Soft Computing 4(1997).

Keywords

Software Quality Parameters, Multi objective Decision Making approach and Genetic Programming.