Abstract
In this paper, we present the results of defect data analysis done with three software companies' defect databases. 11879 software defects were classified and analyzed in order to find out what the real world defect distributions are like and what are the most common defect types. The most common defects in every company were functional defects (65.5%), i.e. defects in computation and/or functional logic. The defect types that were most uncommon were defects due to misunderstood or poorly written requirements (0.2%) or documentation (0.4%).The results of the analysis offer practical data to be used to support Software Process Improvement (SPI). © 2012 Springer-Verlag.
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Raninen, A., Toroi, T., Vainio, H., & Ahonen, J. J. (2012). Defect data analysis as input for software process improvement. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7343 LNCS, pp. 3–16). https://doi.org/10.1007/978-3-642-31063-8_2
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