1. A method comprising: calculating, by a computing device, churn metrics that indicate a degree of change between a first version of code and a second version of the code; calculating, by the computing device for the second version and based on input code metrics that include the churn metrics, second metrics determined from the second version, and first metrics that correspond to the churn metrics and the second metrics that are determined from the first version, a historical variant metric feedback factor that is a sum divided by a total number of the input code metrics, where the sum is a count of each of the input code metrics that exceed a statistical upper bound that is based on the each of the input code metrics' corresponding first metric; and performing, by the computing device and based on the second metrics or on the churn metrics, a logistical regression resulting in a code failure proneness probability for the second version.