International business machines corporation (20240103884). PREDICTIVE LEARNING FOR THE ADOPTION OF SYSTEM CHANGES simplified abstract
Contents
- 1 PREDICTIVE LEARNING FOR THE ADOPTION OF SYSTEM CHANGES
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 PREDICTIVE LEARNING FOR THE ADOPTION OF SYSTEM CHANGES - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Unanswered Questions
- 1.11 Original Abstract Submitted
PREDICTIVE LEARNING FOR THE ADOPTION OF SYSTEM CHANGES
Organization Name
international business machines corporation
Inventor(s)
Tram Thi Mai Nguyen of Santa Clara CA (US)
Prasoon Sinha of Melbourne (AU)
Lee Jason Sanders of West Sussex (GB)
James Raimondo of Santa Clara CA (US)
PREDICTIVE LEARNING FOR THE ADOPTION OF SYSTEM CHANGES - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240103884 titled 'PREDICTIVE LEARNING FOR THE ADOPTION OF SYSTEM CHANGES
Simplified Explanation
The abstract describes a computer-implemented method for evaluating updates to a computing system based on performance data and calculating a confidence score for the update.
- Receiving a request to evaluate an update to a computing system
- Obtaining the current configuration of the computing system
- Identifying changes required by the update to the current configuration
- Obtaining performance data related to the changes from a data repository
- Calculating a confidence score for the update based on the performance data
- Providing the computing system with the confidence score
Potential Applications
This technology could be applied in software development, system maintenance, and IT infrastructure management.
Problems Solved
This technology helps in assessing the impact of updates on a computing system's performance and stability, allowing for informed decision-making.
Benefits
The method provides a quantitative measure (confidence score) for evaluating updates, improving the efficiency and reliability of the update process.
Potential Commercial Applications
The technology could be valuable for software companies, IT service providers, and organizations managing complex computing systems.
Possible Prior Art
One possible prior art could be automated testing tools that assess the impact of software updates on system performance.
Unanswered Questions
How does the method handle complex system configurations?
The abstract does not specify how the method deals with intricate computing system setups and configurations.
What types of performance data are considered in the calculation of the confidence score?
The abstract does not detail the specific performance metrics or data points used in determining the confidence score for the update.
Original Abstract Submitted
according to an aspect, a computer-implemented method includes receiving a request to evaluate an update to a computing system and obtaining a current configuration of the computing system. aspects also include identifying one or more changes that the update will require to the current configuration and obtaining performance data corresponding to the one or more changes from a data repository. aspects further include calculating a confidence score for the update based on the performance data and providing the computing system with the confidence score.
