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TITLE : DETECTION AND EVALUATION OF MAJOR ERROR TRENDS OF SOFTWARE PROJECTS USING PARETO PRINCIPLE AND FUZZY MODEL  
AUTHORS : Chandrakanth G Pujari      Seetharam. K            
ABSTRACT :

Pareto Principle is a statistical method to identify the minority of agents that extent the greatest effect. This principle promotes a win-win situation for the software projects, several organizations want to predict the number of errors in software systems, before they are deployed, to gauge the likely delivered quality and maintenance software. Finding errors in software is a challenging and time and budget consuming task. Minimizing these adverse effects using software error prediction models via guiding testers with defective parts of software system is an attractive research area. In this paper explores many aspects of the Pareto Principle and each aspect is related to detecting major error trends in projects, and examines software error prediction and improve prediction results. And also fuzzy model offers an easy-to-use tool for error evaluation in software projects. The model lies on fuzzy inference. The fuzzy model for error evaluation in software projects is an innovative instrument which can be used to forecast project failure. The model used to develop a software system for evaluating error in an e-testing project, so its applicability was validated.

Keywords: Software projects, Pareto Principle, fuzzy logic, Phase index, Error Index, frequency of errors,
 
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