AI Impact Assessment for Open Source Software Bugs
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Solution Overview
Problem
Current methods lack an automated mechanism to connect open or known bugs of Open-Source Software (OSS) with ongoing operations, leading to numerous incidents due to the absence of a tool that can assess the impact of these bugs on operations and change requests effectively.
Innovation Solution
A method and system for automatic impact assessment of OSS bugs, involving a bug repository and a method of procedures (MOP) repository, where an AI/ML engine matches bug IDs with MOP IDs to identify and present bugs impacting OSS operations, thereby minimizing downtime and enhancing operation safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual validation of MOP and laboratory testing are performed before executing OSS in a live network, then operational safety is improved, but time consumption and labor requirements increase
Solution Approach 1:
The system performs preliminary action by automatically assessing bug impacts before operations are executed. The impact assessment module proactively analyzes known bugs against MOPs and operations to identify potential issues in advance, allowing operations teams to prepare mitigation strategies beforehand rather than reacting to problems after they occur.
Solution Approach 2:
The system enables self-service by automatically connecting bug information with MOPs and operations without requiring manual intervention. The automated impact assessment mechanism independently analyzes relationships between bugs, procedures, and operations, generating assessments that operations teams can directly utilize without extensive manual analysis.
2Productivity
If automated impact assessment is implemented, then productivity is improved, but device complexity increases
Solution Approach 1:
The system applies segmentation by dividing the impact assessment function into distinct modular components: bug repository, MOP repository, impact assessment module, and presentation module. Each component handles a specific aspect of the assessment process independently, making the overall complex system more manageable and easier to implement.
Solution Approach 2:
The impact assessment module serves as an intermediary between the bug repository and MOP repository, and the operations team. It automatically processes information from both repositories, analyzes relationships between bugs and MOPs, and generates actionable assessments, thereby simplifying the interaction required between operations teams and the underlying complex data structures.
3Reliability
If continuous monitoring of OSS bugs is performed, then reliability is improved, but loss of information increases due to the volume of bug data
Solution Approach 1:
The system extracts relevant information by selectively connecting only the bug information that is actually relevant to current operations and MOPs. The impact assessment module filters and extracts only the critical relationships between bugs and operations, presenting only the information that operations teams need to make decisions, rather than overwhelming them with all available bug data.
Solution Approach 2:
The system applies local quality by tailoring the bug information presentation to the specific context of each operation and MOP. Rather than providing a uniform overview of all bugs, the system customizes the assessment results to highlight only the locally relevant bug impacts for each specific operation being performed, making the information more digestible and actionable.
Data Source
AI summary
An automatic impact assessment on operations and change requests (CR) caused by bugs of open-source software (OSS) is described. A bug repository is created for storing information about bugs of OSS. A method of procedures (MOP) repository for storing procedures for addressing the bugs of the OSS is created. The procedures in the MOP repository for addressing the bugs and information about the bugs in the bug repository are analyzed to identify at least one bug resulting in an impact on the operation of the OSS. A MOP Risk Assessment Dashboard is provided for analyzing the procedures in the MOP repository and bugs information in the bug repository. The analysis is performed manually from the MOP Risk Assessment Dashboard, or are analyzed automatically using artificial intelligence. At least one bug is identified and displayed on the MOP Risk Assessment Dashboard.