| 16 | | The above checks could, for example, be performed in the CCMS whenever an author checks a module in. If there are rule breeches, the author gets notified immediately and must correct the content. Only when no further rule breeches exist, the module can be passed on to (human) review. |
| | 16 | The above checks could, for example, be performed in the CCMS whenever an author checks a module in. If there are rule breeches, the author gets notified immediately and must correct the content. Only when no further rule breeches exist, the module can be passed on to (human) review. In this sense, they are online checks, because they are closely integrated into the authoring process. Such automatic checks against so-called //business rules// are common practice in S1000D based aerospace and defense projects. |
| | 17 | |
| | 18 | In other situations, offline checks make sense. Offline checks do not occur at a certain step in the authoring process, but they are applied to an existing set of data. Here are some real-world examples of offline checks: |
| | 19 | * Translation Memory systems are often configured to allow multiple, coexisting translations from the same source, and translators freely use this option. After some time, it is hard to find any modules in the CCMS where all text segments have unambiguous matches in the TM. Thus, automatic translation from the TM can rarely be applied, causing significant extra cost. Offline ambiguity checks in a TM can identify and clean up those duplicates. |
| | 20 | * During [wiki:Public/StartPageMigration migration], it makes sense to check source data first whether it fulfills some minimal requirements to reasonably transform them to a new data model. Modules containing significant structural faults are not transformed but rather assigned to an author for manual transformation. |
