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The use of cross-company fault data for the software fault prediction problem

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The use of cross-company fault data for the software fault prediction problem.pdf (87.22Kb)
Author
Çatal, Çağatay
Type
Article
Date
2016
Language
en_US
Metadata
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Abstract
We investigated how to use cross-company (CC) data in software fault prediction and in predicting the fault labels of software modules when there are not enough fault data. This paper involves case studies of NASA projects that can be accessed from the PROMISE repository. Case studies show that CC data help build high-performance fault predictors in the absence of fault labels and remarkable results are achieved. We suggest that companies use CC data if they do not have any historical fault data when they decide to build their fault prediction models.
Subject
Metrics values
defect prediction
cross-company data
Roc Curves
Classification
Modules
Metrics
URI
https://doi.org/10.3906/elk-1409-137
https://hdl.handle.net/11413/2208
Collections
  • Makaleler / Articles [100]
  • Scopus Publications [724]
  • WoS Publications [1016]

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İstanbul Kültür University

Hakkında |Politika | Kütüphane | İletişim | Send Feedback | Admin

Istanbul Kültür University, Ataköy Campus E5 Karayolu Üzeri Bakırköy 34158, İstanbul / TURKEY
Copyright © İstanbul Kültür University

Creative Commons Lisansı
IKU Institutional Repository, Creative Commons Alıntı-GayriTicari-Türetilemez 4.0 Uluslararası Lisansı ile lisanslanmıştır.

Designed by  UNIREPOS