Performance variability estimator

A computer program product comprising:

• one or more computer readable storage media and program instructions stored on the one or more computer readable storage media, the stored program instructions comprising:
• program instructions to 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;
• program instructions to 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;
• program instructions to 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;
• and
• program instructions to responsive to determining that the regressed build is not due to variability, apply one or more mitigation actions to the regressed build based on one or more similar historical builds.

A computer system comprising:

• one or more computer processors;
• one or more computer readable storage media;
• and
• program instructions stored on the computer readable storage media for execution by at least one of the one or more processors, the stored program instructions comprising:
• program instructions to 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;
• program instructions to 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;
• program instructions to 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;
• and
• program instructions to responsive to determining that the regressed build is not due to variability, apply one or more mitigation actions to the regressed build based on one or more similar historical builds.