Counting the Hidden Defects in Software Documents

This chapter describes a novel application of machine learning to an important estimation problem in software engineering – estimating the number of hidden defects in software artifacts. The number of defects is a software metric that is indispensable for guiding decisions about the software quality assurance during development. In engineering processes, management usually demands that a certain quality level be met for the products at each production step, for instance, that each product be 98 percent defectfree. Software can never be assumed defect-free. In order to assess whether additional quality assurance is required before a prescibed quality level is met, the software engineers must reliably estimate the AbSTRACT