US 12,423,201 B1
Machine learning model training to assist in system debug
Uma Srinivasan, Poughkeepsie, NY (US); Akil Khamisi Sutton, Poughkeepsie, NY (US); Egduard Ramon Jauregui, Aurora, CO (US); and Lisander Lopez, Poughkeepsie, NY (US)
Assigned to INTERNATIONAL BUSINESS MACHINES CORPORATION, Armonk, NY (US)
Filed by INTERNATIONAL BUSINESS MACHINES CORPORATION, Armonk, NY (US)
Filed on Mar. 18, 2024, as Appl. No. 18/607,627.
Int. Cl. G06F 11/00 (2006.01); G06F 11/07 (2006.01); G06F 11/22 (2006.01); G06F 11/26 (2006.01)
CPC G06F 11/2263 (2013.01) [G06F 11/0766 (2013.01); G06F 11/261 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method of facilitating processing within a computing environment, the computer-implemented method comprising:
generating a data set for training a machine learning model to predict fault location in a system, the generating including:
injecting, at a selected location of the system, a test fault into a simulation of the system using a workload;
recording a respective error syndrome generated by the simulation resulting from injecting the test fault into the simulation at the selected location;
repeating injecting, at one or more other selected locations of the system, of one or more other test faults into the simulation of the system using the workload, and the recording of respective error syndromes generated by the simulation resulting from injecting the one or more other test faults into the simulation of the system to generate the data set; and
training, using the data set, the machine learning model to predict fault location within the system; and
providing the trained machine learning model for use in debugging the system, where the debugging includes predicting, using the trained machine learning model, the fault location within the system based on an error syndrome generated by the system due to the fault.