Automating Test Cases via Web Scraping and Element Repository
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Solution Overview
Problem
Current test automation processes require significant manual effort and are prone to errors, as users must write at least a portion of automated tests, which is time-consuming and inefficient.
Innovation Solution
A system and method that uses a web scraper to identify application elements, stores them in a repository, and automatically converts manually written test cases into automated tests by selecting preconfigured test functions using natural language processing or machine learning, eliminating the need for extensive user input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If users manually write automated test cases, then test automation is achieved, but the process is time-consuming and error-prone
Solution Approach 1:
The system performs preliminary scraping of the application to identify and store all elements in a repository before test case creation. This pre-prepared element database eliminates the need for users to manually locate and identify elements when writing automated tests, significantly reducing the time required for test automation while maintaining accuracy.
2Extent of automation
If users manually write automated test cases, then test automation is achieved, but errors increase
Solution Approach 1:
The system introduces an intermediary element repository that acts as a bridge between the application and the automated test cases. This repository stores standardized element information with consistent identifiers and properties, serving as a reliable intermediary that eliminates manual element identification errors and ensures accuracy across all automated test cases.
3Extent of automation
If web scraping is used to identify application elements, then element identification is automated, but system complexity increases
Solution Approach 1:
The system segments the test automation process into distinct modular components: a web scraping module for element identification, a repository module for element storage, and a test case generation module for automated test creation. This segmentation allows each component to be independently developed, maintained, and optimized, reducing overall system complexity while maintaining high automation capabilities.
Data Source
AI summary
As described herein, a system, method, and computer program are provided for automating manually written test cases. In use, a web scraper is used to scrape an application to be tested, wherein the scraping identifies elements of the application. Additionally, a repository is used to store an indication of the elements of the application identified from the scraping of the application. Further, a test case manually written for the application is accessed. One or more of the elements of the application indicated in the repository that are impacted by the manually written test case are then determined. Still yet one or more of the preconfigured test functions that correspond with the one or more of the elements of the application are selected from a library of preconfigured test functions. Moreover, the manually written test case is automated, to form an automated test case, using the selected one or more of the preconfigured test functions.