Code coverage quality estimator

Details Code coverage quality estimator Code coverage quality estimator

2006-07-31

2009-11-10

Beausoliel, Robert (Department: 2113)

Error detection/correction and fault detection/recovery

Data processing system error or fault handling

Reliability and availability

C714S038110, C717S124000, C717S126000

Reexamination Certificate

active

07617415

ABSTRACT:
A method for estimating a quality of code coverage of a test is described. The method includes training a neural network, using the neural network to generate a risk factor for each code element, and determining a coverage quality based on risk factors of executed code elements and risk factors of unexecuted code elements. The neural network is trained by inputting suggestive data as input and error severity data as output. Suggestive data may be data that correlates to a likelihood that a code element contains an error, and the error severity data is an evaluation of a severity of any error that was present in the code element. A coverage quality can be determined based on the risk factors of the code elements tested during the test and the risk factors of the code elements not tested during the test.

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Anderson et al. “Assessing Neural Networks as Guides for Testing Activities.” Proc. of METRICS 1996. copyright 1996.
Lasse Koskela,, “Introduction to Code Coverage”, JavaRanch Journal, Jan. 2004, http://www.javaranch.com
ewsletter/200401/IntroToCodeCoverage.html, pp. 1-14.

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