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Prediction models for software fault correction effort

Authors: William M. Evanco;

Prediction models for software fault correction effort

Abstract

We have developed a model to explain and predict the effort associated with changes made to software to correct faults while it is undergoing development. Since the effort data available for this study is ordinal in nature, ordinal response models are used to explain the effort in terms of measures of fault locality and the characteristics of the software components being changed. The calibrated ordinal response model is then applied to two projects not used in the calibration to examine predictive validity.

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    influence
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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
14
Average
Top 10%
Top 10%
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