DocumentCode :
1705823
Title :
Guiding Testing Activities by Predicting Defect-Prone Parts Using Product and Inspection Metrics
Author :
Elberzhager, Frank ; Kremer, Stephan ; Münch, Jürgen ; Assmann, Danilo
Author_Institution :
Fraunhofer IESE, Kaiserslautern, Germany
fYear :
2012
Firstpage :
406
Lastpage :
413
Abstract :
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.
Keywords :
inspection; program testing; quality assurance; software metrics; software quality; defect-prone parts identification; defect-prone parts prediction; early defect detection activities; inspection defect data; inspection metrics; product metrics; quality assurance; quality information; Complexity theory; Context; Focusing; Inspection; Measurement; Quality assurance; Testing; case study; comparison; focusing; inspection metrics; product metrics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Software Engineering and Advanced Applications (SEAA), 2012 38th EUROMICRO Conference on
Conference_Location :
Cesme, Izmir
Print_ISBN :
978-1-4673-2451-9
Type :
conf
DOI :
10.1109/SEAA.2012.30
Filename :
6328182
Link To Document :
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