World Congress 2023 • Aug 11, 2023

Useful AI friends for developers – building a multilingual app

Andreas Erben , Tim Cadenbach

Why do general LLMs fail at app localization? Discover how to securely combine Copilot, GPT-4, and DeepL to modernize legacy code without inflating token costs.

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#1 about 3 min

Evaluating and sanitizing legacy code artifacts safely

Analyzing unknown project archives automatically prevents malicious code execution in local environments.

#2 about 5 min

Restructuring application interfaces using directed system prompts

Providing strict instructional constraints to generative models ensures accurate programmatic layout adjustments.

#3 about 3 min

Refactoring default UI component names for better readability

Leveraging contextual code completion automates the tedious renaming of autogenerated project variables.

#4 about 3 min

Automating the extraction of static text strings

Migrating hardcoded literal values into structured JSON objects establishes a clean localization foundation.

#5 about 7 min

Mitigating automated translation ambiguities through domain context

Employing specialized translation APIs with custom glossaries eliminates errors caused by isolated wording.

#6 about 5 min

Integrating continuous localization workflows into web frontends

Mapping dictionary keys directly to application components allows seamless generation of multilanguage updates.

#7 about 4 min

Securing proprietary source code when using language models

Utilizing enterprise cloud environments guarantees data privacy policies compared to public generic models.

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