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2006
Report
Titel
Building software inspection effectiveness prediction models using data mining
Titel Supplements
A replicated case study
Abstract
Inspections have been shown to be an effective means of detecting defects early on in the software development life cycle. However, they are not always successful or beneficial as they are affected by a number of technical and managerial factors. To make inspections successful, one important aspect is to understand what the factors are that affect inspection effectiveness in a given environment, based on project data. In this paper we collected data from over 1600 code inspections and replicated a multivariate statistical analysis in order to look at how management factors, such as the effort assigned and the inspection rate, affect inspection effectiveness. Because the functional form of effectiveness models is a priori unknown, we use a novel exploratory analysis technique: Multiple Adaptive Regression Splines (MARS). We compare the MARS model with more classical regression models and compare the results of this study with previous studies.
Verlagsort
Kaiserslautern