Electronic Map Retrieval Testing via Historical Interaction Analysis
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Solution Overview
Problem
Existing electronic map testing methods rely on inherent word tables, which fail to comprehensively cover test scenarios, resulting in a lack of test integrity and inadequate evaluation of upgrade logic.
Innovation Solution
A method and apparatus for map retrieval testing that analyzes historical interaction data from multiple dimensions, generates test data based on this analysis, and uses it to test electronic map retrieval, enabling a more comprehensive and intuitive comparison of different map versions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If inherent word tables are used for test data, then test implementation is simple, but test scenario coverage is insufficient
Solution Approach 1:
The system performs preliminary analysis of historical interaction data before generating test data. By pre-processing real user interaction records and extracting multi-dimensional features (search conditions, result types, user behaviors), the system prepares comprehensive test scenarios in advance, thereby improving test coverage without complicating the actual test execution process
Solution Approach 2:
The system copies and transforms real historical interaction data into test data while preserving key characteristics. By replicating actual user search patterns, query conditions, and interaction behaviors from production environments, the system creates realistic test scenarios that maintain simplicity while significantly enhancing test scenario coverage
2Reliability
If multi-dimensional analysis of historical interaction data is performed, then test data comprehensiveness is improved, but data processing complexity increases
Solution Approach 1:
The system segments the complex data processing task into distinct modules: data collection module, multi-dimensional analysis module (extracting search conditions, result types, user behaviors), data association module, and test data generation module. This segmentation allows comprehensive multi-dimensional analysis while managing complexity through modular architecture, where each module handles specific processing aspects independently
Solution Approach 2:
The system introduces an intermediary data processing layer that sits between historical interaction data and test data generation. This intermediary layer performs multi-dimensional analysis by extracting and associating various data dimensions (search conditions, result types, user behaviors) before passing processed information to test data generation, thereby comprehensively analyzing data while managing complexity through intermediate processing steps
3Ease of operation
If traditional testing methods are used, then testing process is straightforward, but upgrade logic evaluation is inadequate
Solution Approach 1:
The system implements feedback mechanisms by comparing test results across different electronic map versions. By analyzing user interaction data and test outcomes, the system provides feedback on upgrade logic effectiveness, identifying improvements and issues in retrieval accuracy, search performance, and user experience, thereby enhancing evaluation precision while maintaining operational simplicity through automated feedback loops
Solution Approach 2:
The system evaluates upgrade logic by introducing multiple evaluation dimensions beyond traditional testing. By analyzing test data from diverse perspectives (search condition matching, result type accuracy, user behavior patterns, retrieval efficiency), the system comprehensively assesses upgrade logic effectiveness, transforming single-dimension traditional testing into multi-dimensional evaluation that improves measurement precision
Data Source
AI summary
The present application discloses a method, an apparatus, a device and a storage medium for map retrieval test, relating to the fields of intelligent transportation, data retrieval and the like. The specific implementation scheme includes: analyzing historical interaction data of a user and an electronic map, to obtain an analysis result; the analysis result is used for representing the historical interaction data from a plurality of dimensions; associating the historical interaction data with the analysis result used for representing the historical interaction data from the plurality of dimensions, to obtain associated data; generating test data based on the historical interaction data in the associated data and the analysis result representing the historical interaction data from at least one dimension; and testing the electronic map by utilizing the test data, to obtain a test result of the electronic map.