Empirical interval estimates for the defect content after an inspection

Authors:
Frank Padberg
Affiliations:
Fakultät für Informatik Universität Karlsruhe Germany
Venue:
Proceedings of the 24th International Conference on Software Engineering
Year:
2002

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Using Machine Learning for Estimating the Defect Content After an Inspection

IEEE Transactions on Software Engineering

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Abstract

We present a novel method for estimating the number of defects contained in a document using the results of an inspection of the document. The method is empirical, being based on observations made during past inspections of comparable documents. The method yields an interval estimate, that is, a whole range of values which is likely to contain the true value of the number of defects in the document. We also derive point estimates from the interval estimate. The method is validated using a known empirical inspection dataset and clearly outperforms existing approaches for estimating the defect content after inspections.