  Product metrics, such as size or complexity, are often used to identify
defect-prone parts or to focus quality assurance activities. In contrast,
quality information that is available early, such as information provided by
inspections, is usually not used. Currently, only little experience is
documented in the literature on whether data from early defect detection
activities can support the identification of defect-prone parts later in the
development process. This article compares selected product and inspection
metrics commonly used to predict defect-prone parts. Based on initial
experience from two case studies performed in different environments, the
suitability of different metrics for predicting defect-prone parts is
illustrated. These studies revealed that inspection defect data seems to be a
suitable predictor, and a combination of certain inspection and product metrics
led to the best prioritizations in our contexts.
