Revisiting supervised and unsupervised models for effort-aware just-in-time defect prediction

Revisiting supervised and unsupervised models for effort-aware just-in-time defect prediction

Effort-aware just-in-time (JIT) defect prediction aims at finding more defective software changes with limited code inspection cost. Traditionally, supervised models have been used; however, they require sufficient labelled training data, which is difficult to obtain, especially for new projects. Re...

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Bibliographic Details
Main Authors: HUANG, Qiao, XIA, Xin, LO, David
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2018
Subjects:
Evaluation metrics
Defect prediction
Research bias
Software Engineering
Online Access:https://ink.library.smu.edu.sg/sis_research/4355
https://ink.library.smu.edu.sg/context/sis_research/article/5358/viewcontent/Revisting_effort_aware_JIT_DP_emse18_afv.pdf
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Institution: Singapore Management University
Language: English

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https://ink.library.smu.edu.sg/sis_research/4355
https://ink.library.smu.edu.sg/context/sis_research/article/5358/viewcontent/Revisting_effort_aware_JIT_DP_emse18_afv.pdf

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