Hybrid Fuzzy Knowledge Based Prediction Model for the Software Development and Maintenance Quality in Software Engineering Approach
Anusuya Ramasamy1, Abel Adane Changare2
1Dr. Anusuya Ramasamy*, Assistant Professor, Faculty of Computing and Software Engineering, AMIT, Arbaminch University, Ethiopia.
2Mr. Abel Adane Changare, Lecturer, Faculty of Computing and Software Engineering, AMIT, Arbaminch University, Ethiopia.
Manuscript received on July 16, 2020. | Revised Manuscript received on July 22, 2020. | Manuscript published on August 10, 2020. | PP: 316-321 | Volume-9 Issue-10, August 2020 | Retrieval Number: 100.1/ijitee.I7623079920 | DOI: 10.35940/ijitee.I7623.0891020
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The main arena of Software Engineering development with ood design, development, coding, testing, implementation, deployment of the software, finally maintaining the software with good functionality. For the development of software many organizations are investing more and more budget in their revenue. Software Engineering development has several categories of data presented in software engineering such as Graphical User Interface, Usage graphs, writing text, realities and images. Significant information be able to be obtained from this composite data by well recognized data mining techniques such as association, classification, clustering etc. By discovery hidden patterns by data mining software engineering data is made illegal. Software Engineering development has many objectives in software engineering such as Code and Design optimization, Project documentation, Development cost estimation etc. Variety of significant data mining method in each phase of software development life cycle supports in realizing these objectives proficiently and the failure rate of software is decreased. . This paper focused a new hybrid model like combination of Fuzzy Logic and knowledge management offers a significant method for developing models for software quality prediction. This research paper explains about exercise of estimate and valuation at a particular organization by developments and represents the outcomes attained with a fuzzy based classification and knowledge model for the fuzzy knowledge management predication for the quality of software engineering Approach. This result illustrate that the significance of Average Error Evaluation Efficiency observed and used in fuzzy logic is lesser than Average Error Evaluation Efficiency used in another regression multiple regression; while the value of prediction is higher value that other prediction models is used before. Thus Results demonstrate that Hybrid fuzzy knowledge management predication for the quality of software engineering can be used as alternative for predicting the Software Development and Maintenance Quality (SDMQ).
Keywords: Software Quality Prediction, Fuzzy Logic, knowledge management, Software Development.
Scope of the Article: Fuzzy Logic