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Guiding testing activities by predicting defect-prone parts using product and inspection metrics

: Elberzhager, Frank; Kremer, Stephan; Münch, Jürgen; Assmann, Danilo


Cortellessa, Vittorio (Ed.) ; IEEE Computer Society:
38th EUROMICRO Conference on Software Engineering and Advanced Applications, SEAA 2012. Proceedings : 5-8 September 2012, Cesme, Izmir
Los Alamitos: IEEE Computer Society, 2012
ISBN: 978-1-4673-2451-9 (Print)
ISBN: 978-0-7695-4790-9
Conference on Software Engineering and Advanced Applications (SEAA) <38, 2012, Cesme>
Fraunhofer IESE ()
case study; software inspection; fault-prone component; focusing

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.