Early estimation of defect density using an in-process Haskell metrics model

Early estimation of defect density of a product is an important step towards the remediation of the problem associated with affordably guiding corrective actions in the software development process. This paper presents a suite of in-process metrics that leverages the software testing effort to create a defect density prediction model for use throughout the software development process. A case study conducted with Galois Connections, Inc. in a Haskell programming environment indicates that the resulting defect density prediction is indicative of the actual system defect density.