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  A Useful Resource for Defect Prediction Models

Ragneala, R. (2009). A Useful Resource for Defect Prediction Models. Master Thesis, Universität des Saarlandes, Saarbrücken.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0027-BA8D-E Version Permalink: https://hdl.handle.net/11858/00-001M-0000-0027-BA8E-C
Genre: Thesis

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MasterThesis_RoxanaRagneala.pdf (Any fulltext), 4MB
 
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 Creators:
Ragneala, Roxana1, Author           
Zeller, Andreas2, Advisor
Weikum, Gerhard3, Referee           
Affiliations:
1International Max Planck Research School, MPI for Informatics, Max Planck Society, ou_1116551              
2External Organizations, ou_persistent22              
3Databases and Information Systems, MPI for Informatics, Max Planck Society, ou_24018              

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 Abstract: Predicting likely software defects in the future is valuable for project managers when planning resource allocation for software testing. But building prediction models using only code metrics may not be suffice for accurate results. In this work, we investigate the value of code history metrics that can be collected from the project's version archives for the purpose of defect prediction. Our results suggest that prediction models built using code history metrics outperform those using traditional code metrics only.

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Language(s): eng - English
 Dates: 2009-072009
 Publication Status: Issued
 Pages: -
 Publishing info: Saarbrücken : Universität des Saarlandes
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: Ragneala2009
 Degree: Master

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