Mirela
Localization testing verifies that a software product behaves as expected in a specific locale or region. The methodology used in the process, whether automated or manual, can impact the quality, speed, and scalability of the product’s global release. That’s why it’s important to discuss automated vs manual localization testing, because you’ll see when each approach is most effective.
Manual localization testing, the traditional approach
Manual localization testing involves human testers who are either native speakers of the target language or culturally aware of the region in question. These testers examine the product by navigating through the interface, reading the content, and identifying issues that could affect usability or cause offense.
This method of testing has the advantage of being unparalleled when it comes to identifying subtle linguistic nuances, cultural references, and idiomatic expressions. A machine might correctly translate a phrase, but only a human can determine if the phrase resonates with native speakers or if it carries unintended connotations. Manual testing also excels at catching context-specific issues.
However, manual testing is labor-intensive, time-consuming, and prone to human error. The cost of hiring language experts or regional QA testers can get high, especially for applications targeting multiple locales. Plus, it’s not easily scalable, which brings us to the other testing method.
Automated localization testing, a more scalable solution
Automated localization testing uses software tools to verify localized elements in the application. These tools can perform tasks such as checking language files for missing translations, validating date and time formats, and simulating UI layouts across different locales.
Automation speeds things up in the QA process. Once a test suite is set up, it can run across hundreds of locales simultaneously. Automated tests are especially useful for regression testing; they verify that previously working translations or formats haven’t broken due to code changes.
Now, despite these advantages, automated localization testing lacks the depth of human intuition. Sure, scripts can validate string presence and layout integrity, but they cannot assess the appropriateness of translations or cultural nuances. And it may not be cost-effective for small-scale projects or startups that target only a limited number of locales.
Automated vs manual localization testing: the differences
Manual testing excels in some areas, automated testing excels in other areas. You can examine these essential differences best by looking at this table.
| Automated testing | Manual testing | |
| Accuracy | Limited to technical validation | High, because it can catch linguistic and cultural inaccuracies |
| Speed | Very fast, as you can execute tests across multiple locales simultaneously | Slower, because it requires individual testers to check each locale manually |
| Scalability | Highly scalable | Low scalability |
| Initial cost | High | Low |
| Long-term cost | Low | High |
| Best for | Routine checks, regression testing, CI/CD integration | Final validation, nuances content |
| Human judgment | Absent, or not as present | Present |
| Error detection | Good at catching technical/localization file errors and layout issues | Good at detecting language quality, tone issues, and UI bugs |
| Setup time | Can be long | Minimal setup |
| Maintenance | Requires ongoing updates to test scripts as app changes | Less dependent on technical updates, but time-consuming |
When to use each
Sometimes, it’s best to use a hybrid approach. Combine automated and manual testing to maximize the effectiveness of your localization testing. Manual testing is indispensable in the final validation stage before a major release, and it’s also ideal for creative (or heavily contextual) content like marketing copy.
Automation can be leveraged for routine checks, regression testing, and to verify the integrity of localization files. It’s most effective in agile environments with frequent releases, and for businesses targeting dozens or hundreds of languages.