Language Module for Automated UI Text Validation
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Solution Overview
Problem
Current automation tools are inadequate for performing language acceptance testing, as they cannot efficiently execute in a language test mode and generate the necessary artifacts for language testing, leading to a labor-intensive and error-prone manual process.
Innovation Solution
A language module is introduced, comprising a text and tooltip capturing element and a screenshot filtering element, which can be consumed by functional test automation tools to transform them into language test automation tools. This module captures and compares labels, tooltips, and screenshots across different languages, filtering out redundant screenshots to reduce the workload for language testers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual language acceptance testing is performed by dedicated language testers, then translation accuracy and contextual validation can be ensured, but the testing process becomes labor-intensive and time-consuming
Solution Approach 1:
The testing system is segmented into multiple specialized modules: automation tool for functional testing, language module for artifact generation, screenshot filtering element for redundancy removal, and comparison element for translation validation. This segmentation allows each module to specialize in specific tasks, improving both accuracy and efficiency simultaneously.
Solution Approach 2:
A language module acts as an intermediary between the automation tool and the testing process. It captures screenshots and text artifacts during automation execution and transforms them into language-testing-specific artifacts, enabling automated language validation without requiring manual intervention for each screenshot review.
2Productivity
If automation tools are used for functional testing, then testing speed and consistency are improved, but they cannot execute in language test mode or generate necessary language testing artifacts
Solution Approach 1:
The automation tool is enhanced with a language module that provides multi-functionality. The same automation infrastructure that performs functional testing now also captures and generates language testing artifacts, allowing a single tool to serve both functional and language testing purposes without sacrificing either capability.
Solution Approach 2:
The language module performs preliminary actions by capturing screenshots and text artifacts during the automation tool's execution. This preliminary capture of data enables subsequent language-specific analysis and comparison without requiring separate manual screenshot-taking steps.
3Measurement precision
If all screenshots are reviewed manually by language testers, then comprehensive translation validation is achieved, but storage requirements and bandwidth usage increase significantly
Solution Approach 1:
The screenshot filtering element extracts only the essential information needed for language testing by comparing screenshots and identifying unique ones. Redundant screenshots that duplicate previously reviewed content are filtered out and discarded, retaining only the necessary artifacts for comprehensive translation validation.
Solution Approach 2:
The system discards redundant screenshots that provide no additional language validation value while recovering and retaining unique screenshots that contain new translation content. This selective retention minimizes storage requirements while maintaining complete translation validation coverage.
Data Source
AI summary
According to some embodiments, systems and methods are provided including a memory storing program code to: execute a functional automation tool for an application under test in at least two languages, wherein execution of the functional automation tool includes a rendering of a plurality of user interfaces in each of the at least two languages; identify at least one of a label and a tooltip in each of the plurality of user interfaces; capture a screenshot for each of the plurality of user interfaces, wherein the captured screenshots include a first screenshot and at least one subsequent screenshot; identify the subsequent screenshot as unique or redundant; and render a language acceptance testing output for each unique screenshot, displaying each identified label and tooltip in the at least two languages. Numerous other aspects are provided.