DocumentCode
28073
Title
Defect-Density Assessment in Evolutionary Product Development: A Case Study in Medical Imaging
Author
Yang-Ming Zhu ; Faller, D.
Volume
30
Issue
4
fYear
2013
fDate
July-Aug. 2013
Firstpage
81
Lastpage
87
Abstract
Defect density is the ratio between the number of defects and software size. Properly assessing defect density in evolutionary product development requires a strong tool and rigid process support that enables defects to be traced to the offending source code. In addition, it requires waiting for field defects after the product is deployed. To ease the calculation in practice, a proposed method approximates the lifetime number of defects against the software by the number of defects reported in a development period even if the defects are reported against previous product releases. The method uses aggregated code churn to measure the software size. It was applied to two development projects in medical imaging that involved three geographical locations (sites) with about 30 software engineers and 1.354 million lines of code in the released products. The results suggest the approach has some merits and validity, which the authors discuss in the distributed development context. The method is simple and operable and can be used by others with situations similar to ours.
Keywords
medical image processing; software metrics; code churn; defect-density assessment; development projects; distributed development context; evolutionary product development; medical imaging; software size measurement; source code; Analytical models; Approximation methods; Performance evaluation; Software d; Software metrics; Software performance; Software quaility; code churn; defect density; distributed development; evolutionary development;
fLanguage
English
Journal_Title
Software, IEEE
Publisher
ieee
ISSN
0740-7459
Type
jour
DOI
10.1109/MS.2012.111
Filename
6253198
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