Automated Support Query Generation from Source Code Context
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Solution Overview
Problem
Automated support systems often fail to provide accurate solutions to users experiencing software errors due to the lack of appropriate keywords in user queries, as users may not know the correct keywords to identify the solution.
Innovation Solution
The method involves generating a support query based on context information from the source code of the application encountering an error, which can be either hard-coded or generated using a template with variables, to create a precise query that can be used by automated support systems to retrieve solutions from a knowledge database.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users enter queries manually into automated support systems, then users can access potential solutions without communicating with a real person, but users may not know the correct keywords to identify the solution
Solution Approach 1:
The system automatically generates the support query using context information from the error and source code, eliminating the need for users to manually construct accurate technical queries. The application itself serves to create the query that it then submits to the support system.
Solution Approach 2:
The system introduces an intermediary query generation process that translates raw error context into formatted support queries with appropriate keywords. This intermediary layer bridges the gap between user errors and support database searches.
2Productivity
If automated support systems rely on user-provided queries, then users have access to support solutions, but the solutions may not be accurate due to lack of context information
Solution Approach 1:
The system performs preliminary actions by collecting and analyzing context information from the error and source code before submitting the query to the support system. This preliminary data gathering ensures the query contains sufficient information for accurate solution retrieval.
Solution Approach 2:
The system uses feedback from the error context and source code analysis to refine and format the support query, ensuring it contains the necessary keywords and information for accurate solution matching in the support database.
3Adaptability or versatility
If users with less technical knowledge attempt to formulate support queries, then they can access automated support, but they cannot produce accurate queries to identify solutions
Solution Approach 1:
The system performs the query formulation task automatically using the error context and source code, making the process self-serving and eliminating the need for users to possess technical query formulation skills.
Solution Approach 2:
Instead of requiring users to translate their problems into technical queries, the system inverts the process by automatically generating the query from the error context, reversing the traditional query formulation direction.
Data Source
AI summary
Support queries are automatically provided. An error is identified during execution of an application. A support query for the error is produced using the source code for the application with the support query including context information for the error. The support query is displayed to a user.


