Machine Learned Decision Guidance for Alerts Originating from Monitoring Systems

A system, comprising:

• at least one processing unit;
• and
• a memory storing computer executable instructions that, when executed by the at least one processing unit, cause the system to perform a method for detecting occurrences of issues in a software system, comprising:
• receiving information about a detected issue;
• comparing a fingerprint of the detected issue to one or more fingerprints of previously detected issues to determine whether the detected issue is new;
• when it is determined that the detected issue is new:
• storing the information about the detected issue in a storage device;
• providing the information about the detected issue to a feature generation component that generates a feature vector for the detected issue;
• providing the feature vector to an evaluation component that analyzes the feature vector to determine a probability that the detected issue is a bug;
• and
• providing an ordered list of detected issues.

A computer-readable storage medium storing computer executable instructions that, when executed by a processing unit, causes the processing unit to perform a method, comprising:

• generating a feature vector for a detected issue using information associated with the detected issue;
• providing the feature vector to one or more models of an evaluation component;
• causing the one or more models of the evaluation component to analyze the feature vector to determine a probability that the detected issue is a bug;
• reporting the occurrence of the detected issue;
• receiving a fix to the detected issue;
• and
• updating at least one of the one or more models using the fix to the detected issue.