Research Article |
Optimization of Software Quality Attributes using Evolutionary Algorithm
Author(s) : Priyanka Makkar1, Sunil Sikka2 and Anshu Malhotra3
Published In : International Journal of Electrical and Electronics Research (IJEER) Volume 10, Issue 2 , Special Issue on RDCTML
Publisher : FOREX Publication
Published : 22 May 2022
e-ISSN : 2347-470X
Page(s) : 131-137
Abstract
Software quality is a multidimensional concept. Single attribute can’t define the overall quality of the software. Software developer aims to develop software that possesses maximum software quality which depends upon various software quality attributes such as understand ability, flexibility, reusability, effectiveness, extendibility, functionality, and many more. All these software quality attributes are linked with each other and conflicting in nature. Further, these quality attributes depend upon the design properties of the software. During the designing phase of software, developers must optimize the design properties to develop good software quality. To obtain the appropriate value optimization is done. This paper implemented two multi-objective evolutionary algorithms (NSGA-2 and MOEA/D) to optimize software design properties to enhance software quality. While comparing NSGA-2 algorithm with original values it is found that there is a 1.73% improvement in the software quality on the other hand MOEA/D shows a 3.58% improvement in the software quality.
Keywords: Software Metrics
, Software Quality
, Software Quality Attributes
, QMOOD
Priyanka Makkar, Research Scholar, Department of Computer Science, Amity University Haryana, India; Email: priyanka.makkar@rediffmail.com
Sunil Sikka, Associate Professor, Department of Computer Science, Amity University Haryana, India; Email: ssikka@ggn.amity.edu
Anshu Malhotra, Associate Professor, Department of Computer Science, The NorthCap University, Gurugram, India; Email: anshumalhotra@ncuindia.edu
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Priyanka Makkar, Sunil Sikka and Anshu Malhotra (2022), Optimization of Software Quality Attributes using Evolutionary Algorithm. IJEER 10(2), 131-137. DOI: 10.37391/IJEER.100214.