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. Categories and Subject Descriptors D.2.8 [Software Engineering]: Metrics - Performance measures, Process metrics, Product metrics. General Terms Measurement, Reliability. Keywords Empirical software engineering, multiple regression, software quality, Haskell.

• Type: Conference
• Year: 2005
• Where: AMOST
• Authors: Mark Sherriff, Nachiappan Nagappan, Laurie A. Williams, Mladen A. Vouk
• Keywords: AMOST 2005, Defect Density, Defect Density Prediction, Software Development Process, Software Engineering