International Business Machines Corporation
PERFORMANCE VARIABILITY ESTIMATOR

Abstract:

One or more computer processors identify one or more similar, historical regression tests and historical builds utilizing a computed similarity measure between a regressed build and one or more historical builds conducted on a same release cycle, wherein the identified one or more similar historical regression tests and historical builds are K closest neighbors to the regressed build; predict an elapsed time of the one or more profiled regression tests utilizing a KNN algorithm comprising the K closest neighbors each weighted by a corresponding average distance from a test point and the elapsed time as a target variable; responsive to the predicted elapsed time exceeding an actual elapsed time associated with the regressed build, determine that the regressed build is an actual regression; responsive to determining that the regressed build is not due to variability, apply one or more mitigation actions to the regressed build.