scholarly journals Software Defect Content Estimation: A Bayesian Approach

2006 ◽  
Author(s):  
Achin Jain ◽  
Alok Patnaik ◽  
Pulak Dhar ◽  
Vineet Srivastava
Keyword(s):  
Bayesian Approach ◽  
Software Defect ◽  
Defect Content ◽  
Defect Content Estimation

A comprehensive evaluation of capture-recapture models for estimating software defect content

2000 ◽  
Vol 26 (6) ◽  
pp. 518-540 ◽  
Author(s):  
L.C. Briand ◽  
K. El Emam ◽  
B.G. Freimut ◽  
O. Laitenberger
Keyword(s):  
Comprehensive Evaluation ◽  
Software Defect ◽  
Defect Content ◽  
Capture Recapture

A Literature Review Study of Software Defect Prediction using Machine Learning Techniques

2018 ◽  
Vol 6 (6) ◽  
pp. 300 ◽  
Author(s):  
Feidu Akmel ◽  
Ermiyas Birihanu ◽  
Bahir Siraj
Keyword(s):  
Machine Learning ◽  
Software Metrics ◽  
Quality Standard ◽  
Machine Learning Techniques ◽  
Software Systems ◽  
Health Care Insurance ◽  
Software Defect ◽  
Learning Techniques ◽  
Software Product

Software systems are any software product or applications that support business domains such as Manufacturing,Aviation, Health care, insurance and so on.Software quality is a means of measuring how software is designed and how well the software conforms to that design. Some of the variables that we are looking for software quality are Correctness, Product quality, Scalability, Completeness and Absence of bugs, However the quality standard that was used from one organization is different from other for this reason it is better to apply the software metrics to measure the quality of software. Attributes that we gathered from source code through software metrics can be an input for software defect predictor. Software defect are an error that are introduced by software developer and stakeholders. Finally, in this study we discovered the application of machine learning on software defect that we gathered from the previous research works.

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