Template-Based Software Bug Query Method
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Solution Overview
Problem
Software developers and maintainers face challenges in accurately finding relevant information for software bugs due to the complexity of search requirements and the reliance on keyword matching in traditional relational databases, leading to inefficient and inaccurate search results.
Innovation Solution
A template-based automatic question and answer method that extracts entity relationship triples from bug reports, uses natural language patterns to identify entities and construct query templates, and employs SPARQL queries to improve understanding and retrieval of software bug information, reducing the search space and enhancing accuracy and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If keyword matching technology is used to search software bug information, then the search can cover a wide range of information, but the search space becomes large, time is greatly consumed, and the accuracy of search results deteriorates
Solution Approach 1:
The patent segments the search process into multiple stages: first extracting entity relationship triples from the bug report to identify key elements, then using these entities to generate targeted query templates. This segmentation allows the system to focus search efforts on relevant portions of the bug database rather than performing broad keyword matching across all information, thereby reducing search time while maintaining comprehensive coverage.
Solution Approach 2:
The patent performs preliminary analysis by extracting entity relationship triples and generating query templates before actually executing the search. This preliminary action prepares targeted queries in advance based on the structure and key elements of the bug report, allowing the search to proceed efficiently with pre-formulated questions rather than relying on time-consuming keyword matching during the search execution phase.
2Adaptability or versatility
If keyword matching technology is used to search software bug information, then various information can be retrieved, but the accuracy of search results deteriorates due to large search space
Solution Approach 1:
The patent applies local quality by focusing search efforts on specific, relevant portions of the bug database identified through entity relationship extraction. Instead of uniformly searching all information with keyword matching, the system identifies key entities and their relationships, then directs targeted queries to specific areas of the database that are most likely to contain relevant answers, thereby improving accuracy without sacrificing retrieval capability.
Solution Approach 2:
The patent introduces query templates as an intermediary between the bug report and the bug database search. These templates act as a mediator that translates the extracted entity relationships into structured, semantically meaningful queries. This intermediary layer ensures that searches are conducted with precise intent and context, improving result accuracy while maintaining the ability to retrieve diverse information.
3Quantity of substance
If traditional relational database search method is used, then software bug databases can store comprehensive information, but the search results contain large amount of irrelevant information and attributes
Solution Approach 1:
The patent extracts entity relationship triples from the bug report to identify the specific key elements and relationships that are relevant to the search. By taking out only these essential entities and relationships, the system can formulate targeted queries that retrieve only the most relevant information from the comprehensive bug database, filtering out large amounts of irrelevant attributes and data while maintaining access to the full information storage capacity.
4Measurement precision
If template-based automatic question and answer method is used, then the accuracy of understanding software bug information is improved, but the device complexity increases
Solution Approach 1:
The patent implements self-service by automatically extracting entity relationship triples from bug reports and autonomously generating appropriate query templates based on these extractions. The system serves itself by transforming unstructured bug information into structured queries without requiring manual intervention or complex configuration, thereby improving understanding accuracy while limiting complexity growth through automation rather than manual processes.
Data Source
AI summary
Disclosed is a template-based automatic question and answer method for software bug. An entity relationship triple is extracted from a bug corpus and a natural language pattern is acquired; an entity relationship in the triple is determined; a query template corresponding to the natural language pattern is acquired; an entity in a question q proposed by a user is replaced with an entity type to acquire a question q′; then, the entity type in q′ and an entity type in the natural language pattern are compared and searched for and a similarity is calculated; then, a SPARQL query pattern of the question q is acquired according to the similarity and the entity in the question q; and finally, the SPARQL query pattern of the question q is executed so as to acquire an answer to the question q.