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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
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  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

    	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"


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.


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