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IAAI Articles AI-Based Software Defect Predictors: Applications and Benefits in a Case Study

By Ayse Tosun Misirli, Ayse Bener and Resat Kale

Abstract

n Software defect prediction aims to reduce software testing efforts by guiding testers through the defect-prone sections of software systems. Defect predictors are widely used in organizations to predict defects in order to save time and effort as an alternative to other techniques such as manual code reviews. The usage of a defect prediction model in a real-life setting is difficult because it requires software metrics and defect data from past projects to predict the defect-proneness of new projects. It is, on the other hand, very practical because it is easy to apply, can detect defects using less time, and reduces the testing effort. We have built a learning-based defect prediction model for a telecommunication

Year: 2013
OAI identifier: oai:CiteSeerX.psu:10.1.1.370.9952
Provided by: CiteSeerX
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