Patent ID: 7617415

Claim:
A computer-implemented method for estimating a quality of code coverage of a test, the estimating being executed by a processor, the method comprising: training a neural network by placing the neural network in a learning mode and inputting suggestive data as input and error severity data as output, the output being presented to the neural network when the neural network is in the learning mode, the suggestive data comprising 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; using the neural network to generate a risk factor for each code element, the risk factor being a value representing a likelihood and severity of an error in the code element; identifying code elements tested during the test; determining a coverage quality 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; storing the coverage quality to a machine readable medium; wherein the suggestive data and the error severity data being historical data of at least one computer programming projects.