Cloud Localization Framework Using Extracted UI Strings
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Solution Overview
Problem
Cloud-based applications face challenges in efficiently translating user interface text into multiple languages due to the complexity of integrating multiple code repositories and the need for manual effort, which can lead to errors and security concerns when third-party translators access the entire code base.
Innovation Solution
A framework that provides native language files to third-party translators without exposing the source code, automates translation integration, and includes a localization framework to monitor changes, perform initial checks, and deploy a test build for verification before production.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If third-party translators are given access to the entire code base to translate user interface text, then translation completeness is improved, but security risks and manual effort increase
Solution Approach 1:
The patent extracts only the necessary information (user interface text strings) from the code base and provides it to translators through a controlled interface. The translation framework pulls text from resources, allows translators to work on extracted strings, and returns translated versions without exposing the underlying code structure, thereby maintaining security while enabling complete translation.
Solution Approach 2:
The translation framework acts as an intermediary between the code base and translators. It provides a controlled interface that delivers only the text strings needed for translation while preventing direct access to source code. The framework manages the translation process, handles file operations, and integrates results back into the application without exposing sensitive information.
2Reliability
If manual translation and integration is performed, then translation quality can be controlled, but time consumption and error rates increase
Solution Approach 1:
The framework performs preliminary actions by automatically extracting all user interface text strings from the code base before translation begins. It prepares the text data in advance, organizes it by resource files, and makes it readily available to translators. This preliminary preparation eliminates repetitive manual extraction tasks during translation and reduces overall time consumption while maintaining quality control.
Solution Approach 2:
The translation framework incorporates feedback mechanisms where translators can submit translated strings, and the system validates and integrates these translations back into the code base. The framework provides feedback on translation status, tracks progress, and ensures consistent integration. This feedback loop maintains translation quality while automating the integration process, reducing manual intervention time.
3Loss of information
If multiple code repositories are integrated for localization, then translation coverage is improved, but system complexity increases
Solution Approach 1:
The translation framework is designed with universality to handle multiple code repositories through a single unified interface. It can extract text from various repository locations, manage different resource file formats, and coordinate translation across distributed code bases. This multi-functional design provides comprehensive translation coverage while abstracting away the complexity of managing multiple repositories through a consistent, standardized approach.
4Productivity
If the translation process is automated, then productivity is improved, but verification and validation become more difficult
Solution Approach 1:
The framework incorporates feedback mechanisms where translators can submit translated strings, and the system validates and integrates these translations back into the code base. The framework provides feedback on translation status, tracks progress, and ensures consistent integration. This feedback loop maintains translation quality while automating the integration process, reducing manual intervention time.
Data Source
AI summary
In certain embodiments, a method includes obtaining a cloud-based application; extracting native language files and internationalization keys that correspond to the native language files from the cloud-based application; storing the native language files and the keys in a translation data repository accessible by a translation service; detecting non-native language files corresponding to the native language files in the translation data repository; performing an initial check on the non-native language files; generating, when the initial check passes, a test build of the cloud-based application; deploying the test build to a test environment in a cloud infrastructure to have a first validation performed by the translation service and a second validation performed by a cloud-based application provider; and generating, when the first validation and the second validation pass, a production build of the cloud-based application comprising the non-native language files.