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Understanding the sources of variation in software inspections
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Source ACM Transactions on Software Engineering and Methodology (TOSEM) archive
Volume 7 ,  Issue 1  (January 1998) table of contents
Pages: 41 - 79  
Year of Publication: 1998
ISSN:1049-331X
Authors
Adam Porter  Univ. of Maryland, College Park
Harvey Siy  Univ. of Maryland, College Park
Audris Mockus  Bell Labs, Naperville, IL
Lawrence Votta  Bell Labs, Naperville, IL
Publisher
ACM  New York, NY, USA
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ABSTRACT

In a previous experiment, we determined how various changes in three structural elements of the software inspection process (team size and the number and sequencing of sessions) altered effectiveness and interval. Our results showed that such changes did not significantly influence the defect detection rate, but that certain combinations of changes dramatically increased the inspection interval. We also observed a large amount of unexplained variance in the data, indicating that other factors must be affecting inspection performance. The nature and extent of these other factors now have to be determined to ensure that they had not biased our earlier results. Also, identifying these other factors might suggest additional ways to improve the efficiency of inspections. Acting on the hypothesis that the “inputs” into the inspection process (reviewers, authors, and code units) were significant sources of variation, we modeled their effects on inspection performance. We found that they were responsible for much more variation in detect detection than was process structure. This leads us to conclude that better defect detection techniques, not better process structures, are the key to improving inspection effectiveness. The combined effects of process inputs and process structure on the inspection interval accounted for only a small percentage of the variance in inspection interval. Therefore, there must be other factors which need to be identified.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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CITED BY  14

Collaborative Colleagues:
Adam Porter: colleagues
Harvey Siy: colleagues
Audris Mockus: colleagues
Lawrence Votta: colleagues