Error Handling Recommendation Engine for Software Troubleshooting
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Solution Overview
Problem
Software troubleshooting for proprietary software packages can be time-consuming and difficult due to the lack of accessible troubleshooting instructions, especially when users are unsure which collaborative messaging systems to search or do not have access to them.
Innovation Solution
An error handling recommendation engine that receives error messages, retrieves relevant message threads from collaborative messaging systems like Slack and Microsoft Teams using APIs, generates vector representations, and uses machine learning to match and recommend solutions, generating updated code to fix issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If users search for troubleshooting instructions on collaborative messaging systems, then they may find solutions to errors, but the process becomes extremely time-consuming
Solution Approach 1:
The system performs preliminary actions by proactively monitoring error messages generated during software execution and automatically searching collaborative messaging systems for relevant troubleshooting information before the user needs it. The error handling recommendation engine captures error messages via webhooks, generates queries, and retrieves potential solutions in advance, so when users encounter errors, solutions are already prepared and ready for immediate presentation.
Solution Approach 2:
The error handling recommendation engine serves as an intermediary between the software execution environment and collaborative messaging systems. It automatically bridges the gap by monitoring error messages, formulating search queries, retrieving relevant threads from messaging systems, and presenting filtered solutions to users. This intermediary eliminates the need for users to manually navigate multiple messaging channels and manually search for solutions.
2Reliability
If users manually search multiple collaborative messaging systems and channels, then they may find error solutions, but the complexity of the process increases
Solution Approach 1:
The system merges multiple collaborative messaging systems and channels into a single unified search interface. The error handling recommendation engine simultaneously queries multiple messaging systems (e.g., Slack, Microsoft Teams) and consolidates results, presenting a unified set of relevant solutions to the user. This merging eliminates the need for users to manually navigate through multiple separate systems and channels.
Solution Approach 2:
The system performs self-service by automatically executing the entire troubleshooting search process without user intervention. The error handling recommendation engine autonomously captures error messages, generates search queries, queries multiple messaging systems, filters results based on relevance, and presents solutions. This self-service capability eliminates the manual effort and complexity users would otherwise face in searching multiple systems.
3Ease of operation
If users do not have access to collaborative messaging systems or know which channels to search, then they cannot find solutions, but providing universal access increases system complexity
Solution Approach 1:
The error handling recommendation engine acts as an intermediary that handles all interactions with collaborative messaging systems on behalf of users. It manages authentication, channel selection, and query formulation internally, so users never need to directly access or understand the complexity of messaging systems. The engine translates user error messages into appropriate queries and retrieves solutions without requiring users to navigate the underlying system architecture.
Solution Approach 2:
The system creates a simplified copy or representation of the collaborative messaging systems' troubleshooting information that is accessible to all users regardless of their actual access rights. Instead of requiring users to directly query complex messaging systems, the error handling recommendation engine retrieves and presents relevant error solutions in a simplified format, effectively copying the essential troubleshooting information in an accessible manner.
Data Source
AI summary
Systems and methods are disclosed herein for recommending solutions to execution errors of software packages. An error message related to compilation or execution of computer code is received and, based on a vector representation of the error message and vector representations corresponding to message threads from one or more collaborative messaging systems, a set of message threads that match the error message is identified. Furthermore, a known error message that matches the set of message threads is identified and updated computer code is generated based on the known error message. The updated computer code is then provided to a client device.