Providing cognitive intelligence across continuous delivery pipeline data
US10901876B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 20, 2019 |
| Grant date | Jan 26, 2021 |
| Priority date | — |
| Expiry date | Nov 20, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F11/3438
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method, system and computer program product for detecting potential failures in a continuous delivery pipeline. A machine learning model is created to predict whether changed portion of codes under development at various stages of the continuous delivery pipeline will result in a pipeline failure. After creating the machine learning model, log file(s) may be received that were generated by development tool(s) concerning a changed portion of code under development at a particular stage of the continuous delivery pipeline. The machine learning model provides relationship information between the log file(s) and the changed portion of code. A message is then generated and displayed based on this relationship information, where the message may provide a prediction or a recommendation concerning potential failures in the continuous delivery pipeline. In this manner, the potential failures in the continuous delivery pipeline may be prevented without requiring context switching.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.