DocumentCode :
2164465
Title :
The application of capture-recapture log-linear models to software inspections data
Author :
Kamel, Amr ; Sorenson, P.G.
Author_Institution :
Dept. of Comput. Sci., Alberta Univ., Edmonton, Alta., Canada
fYear :
2003
fDate :
30 Sept.-1 Oct. 2003
Firstpage :
213
Lastpage :
222
Abstract :
Re-inspection has been deployed in industry to improve the quality of software inspections. The number of remaining defects after inspection is an important factor affecting whether to re-inspect the document or not. Models based on capture-recapture (CR) sampling techniques have been proposed to estimate the number of defects remaining in the document after inspection. Several publications have studied the robustness of some of these models using software engineering data. Unfortunately, most of the existing studies did not examine the log linear models with respect software inspection data. In order o explore the performance of the log linear models, we evaluated their performance for three person inspection teams. Furthermore, we evaluated the models using an inspection data set that was previously used to asses different CR models. Generally speaking, the study provided very promising results. According to our results, the log linear models proved to be more robust that all CR based models previously assessed for three-person inspections.
Keywords :
inspection; software fault tolerance; software performance evaluation; software quality; software reliability; CR model; capture-recapture models; estimate the number of defects; inspection data set; inspection teams; inspections data; log linear models; log-linear models; quality of software inspections; software defects; software engineering data; software inspection; Animals; Application software; Chromium; Computer industry; Inspection; Robustness; Sampling methods; Software engineering; Software quality;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Empirical Software Engineering, 2003. ISESE 2003. Proceedings. 2003 International Symposium on
Print_ISBN :
0-7695-2002-2
Type :
conf
DOI :
10.1109/ISESE.2003.1237980
Filename :
1237980
Link To Document :
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