DocumentCode
2038420
Title
A defect estimation approach for sequential inspection using a modified capture-recapture model
Author
Chang, Ching-Pao ; Lv, Jia-Lyn ; Chu, Chih-Ping
Volume
1
fYear
2005
fDate
26-28 July 2005
Firstpage
41
Abstract
Defect prediction is an important process in the evaluation of software quality. To accurately predict the rate of software defects can not only facilitate software review decisions, but can also improve software quality. In this paper, we have provided a defect estimation approach, which uses defective data from sequential inspections to increase the accuracy of estimating defects. To demonstrate potential improvements, the results of our approach were compared to those of two other popular estimation approaches, the capture-recapture model and the re-inspection model. By using the proposed approach, software organizations may increase the accuracy of their defect predictions and reduce the effort of subsequent inspections.
Keywords
inspection; program testing; software development management; software process improvement; software quality; capture-recapture model; defect predictions; defective data; reinspection model; sequential inspection; software defect estimation; software organization; software quality evaluation; Animals; Biological system modeling; Chromium; Computational biology; Costs; Inspection; Maximum likelihood detection; Maximum likelihood estimation; Predictive models; Software quality; and re-inspection model; capture-recapture model; defect estimation; inspection;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Software and Applications Conference, 2005. COMPSAC 2005. 29th Annual International
ISSN
0730-3157
Print_ISBN
0-7695-2413-3
Type
conf
DOI
10.1109/COMPSAC.2005.19
Filename
1509995
Link To Document