Computing Reviews
Today's Issue Hot Topics Search Browse Recommended My Account Log In
Review Help
Search
Balancing privacy and utility in cross-company defect prediction
Peters F., Menzies T., Gong L., Zhang H. IEEE Transactions on Software Engineering39 (8):1054-1068,2013.Type:Article
Date Reviewed: Oct 18 2013

Cross-company defect prediction (CCDP) uses quality assessment data from multiple companies to predict defects in software under development. The advantages of access to rich data sources outside one’s own company must be balanced with data privacy protections for the companies that are willing to share such data. Research and practice in CCDP have largely been inhibited by the difficulties of guaranteeing some level of data privacy to participating companies.

This insightful paper proposes an approach for CCDP privacy that combines the use of an instance pruner (CLIFF) with an instance mutator (MORPH) on a large contributed dataset. A well-designed experiment provides clear evidence that this combination of privatization techniques results in a dataset that provides both effective defect prediction and a high level of privacy for the contributing companies. Experimental results confirm that the proposed CCDP privacy algorithm offers better performance for both utility and privacy measures than other commonly used privacy algorithms, and better performance than the use of the mutator algorithm alone.

The authors hope that these promising results will encourage more companies to share quality assessment data to support the research and practice of CCDP, with an eventual goal of building general software engineering models for industry-wide application to large-scale system development projects. However, the question remains: with the inability to guarantee 100 percent data privacy in any realistic environment, will companies have sufficient trust to participate in CCDP projects regardless of the proven effectiveness of data privacy approaches?

Reviewer:  A. Hevner Review #: CR141649 (1312-1109)
Bookmark and Share
 
Testing And Debugging (D.2.5 )
 
 
Arrays (E.1 ... )
 
 
Privacy (K.4.1 ... )
 
 
Software (K.2 ... )
 
Would you recommend this review?
yes
no
Other reviews under "Testing And Debugging": Date
Software defect removal
Dunn R., McGraw-Hill, Inc., New York, NY, 1984. Type: Book (9789780070183131)
Mar 1 1985
On the optimum checkpoint selection problem
Toueg S., Babaoglu O. SIAM Journal on Computing 13(3): 630-649, 1984. Type: Article
Mar 1 1985
Software testing management
Royer T., Prentice-Hall, Inc., Upper Saddle River, NJ, 1993. Type: Book (9780135329870)
Mar 1 1994
more...

E-Mail This Printer-Friendly
Send Your Comments
Contact Us
Reproduction in whole or in part without permission is prohibited.   Copyright 1999-2024 ThinkLoud®
Terms of Use
| Privacy Policy