Software Testing, Verification and Reliability 20 (2): 89-120 (2010)

Finding Failures from Passed Test Cases:
Improving the Pattern Classification Approach
to the Testing of Mesh Simplification Programs

W.K. Chan 2 , Jeffrey C.F. Ho 3 , and T.H. Tse 4

[paper from Wiley InterScience | technical report TR-2009-03]


Mesh simplification programs create three-dimensional polygonal models similar to an original polygonal model, and yet use fewer polygons. They produce different graphics even though they are based on the same original polygonal model. This results in a test oracle problem. To address the problem, our previous work has developed a technique that uses a reference model of the program under test to train a classifier. Using such an approach may mistakenly mark a failure-causing test case as passed. It lowers the testing effectiveness of revealing failures. This paper suggests piping the test cases marked as passed by a statistical pattern classification module to an analytical metamorphic testing module. We evaluate our approach empirically using three subject programs with over 2700 program mutants. The result shows that, using a resembling reference model to train a classifier, the integrated approach can significantly improve the failure detection effectiveness of the pattern classification approach. We also explain how metamorphic testing in our design trades specificity for sensitivity.

Keywords: test oracle problem, mesh simplification, non-testable software, metamorphic testing, classification, testing methodology.

1. This research is supported in part by GRF grants of the Research Grants Council of Hong Kong (project nos. 123207 and 716507), a grant from City University of Hong Kong (project no. CityU 7002324), and a discovery grant of the Australian Research Council (project no.DP0984760).
2. (Corresponding author.)
Department of Computer Science, City University of Hong Kong, Tat Chee Avenue, Hong Kong.
3. wwwins Consulting Hong Kong Limited, Hong Kong.
4. Department of Computer Science, The University of Hong Kong, Pokfulam, Hong Kong.


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