ACM Home Page
Please provide us with feedback. Feedback
Multivariate visualization in observation-based testing
Full text PdfPdf (316 KB)
Source International Conference on Software Engineering archive
Proceedings of the 22nd international conference on Software engineering table of contents
Limerick, Ireland
Pages: 116 - 125  
Year of Publication: 2000
ISBN:1-58113-206-9
Authors
David Leon  Electrical Engineering and Computer Science Department, Case Western Reserve University, Olin Building, Cleveland, Ohio
Andy Podgurski  Electrical Engineering and Computer Science Department, Case Western Reserve University, Olin Building, Cleveland, Ohio
Lee J. White  Electrical Engineering and Computer Science Department, Case Western Reserve University, Olin Building, Cleveland, Ohio
Sponsors
IEEE-CS : Computer Society
SIGSOFT: ACM Special Interest Group on Software Engineering
Irish Comp Soc : Irish Computer Society
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 17,   Downloads (12 Months): 62,   Citation Count: 14
Additional Information:

abstract   references   cited by   index terms   collaborative colleagues  

Tools and Actions: Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/337180.337195
What is a DOI?

ABSTRACT

We explore the use of multivariate visualization techniques to support a new approach to test data selection, called observation-based testing. Applications of multivariate visualization are described, including: evaluating and improving synthetic tests; filtering regression test suites; filtering captured operational executions; comparing test suites; and assessing bug reports. These applications are illustrated by the use of correspondence analysis to analyze test inputs for the GNU GCC compiler.


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.

 
1
Borg, I. and Groenen, P. Modern Multidimensional Scaling: Theory and Applications, Springer, 1997.
 
2
GCC. The GCC Home Page, http://www.gnu.org/software/gcc/gcc.html, Free Software Foundation, 1999.
 
3
Greenacre, M.J. Theory and Applications of Correspondence Analysis, Academic Press, 1984.
4
5
6
 
7
Harville, D.A. Matrix Algebra From a Statistician's Perspective. Springer-Verlag, 1997.
 
8
9
10
11
12
13
 
14
X.Org. http://www.x.org/, X.Org, 1999.

CITED BY  14

Collaborative Colleagues:
David Leon: colleagues
Andy Podgurski: colleagues
Lee J. White: colleagues