1. Adobe Creative Cloud Ecosystem
Thanks, glad…
This is a growing project, now about 12 months
Credits to team who did not make it
From Zero Lines of Code to a Collection of Global Products in Six Months
Artwork credits: all artwork in this presentation is derived from materials available on Adobe’s Creative Cloud site and the Adobe Globalization team’s intranet

2. - Group engages many new apps - Projects are regular and similar - Scope is widening - International team remains relatively the same in size
adobe’s globalization organization

3. Creative Cloud Ecosystem
I will talk at the beginning about the history of Creative Cloud, the stated 2014 challenge of customer acquisition and conversion, as well as the development and release timelines.
SDK for 3rd party developers
Sign-in component (Adobe ID) to retain users

4. AdobeCreativeSDKFoundation CreativeSDKFoundationAssets CreativeSDKFoundationAuth AdobeSDKDevice AdobeCreativeSDKBehance AdobeCreativeSDKColor CreativeSDKImage

5. Early times long long ago: November 2013
Adobe Ideas
5 locales
iPhone/iPad
Photoshop Touch
3-7 locales
iPhone, then iPad + later Android tablet and phone
Where we started in 2013
- 2 apps, only a few locales, iOS only

6. 2014-2015 capture iOS, Android, Web design and Illustration
phone and tablet targets
4-35 locales each
360+ locales total shipping or planned soon
design and Illustration
video and presentation
And where we are now…
Aviary
digital editing
community
…and more coming!

7. CC Ecosystem projects:
- Common business purpose - Only partly centralized - Fast - Overlapping but not the same GEO coverage - Integrated with other mobile and desktop products
CC Ecosystem projects:
I may remove this slide, but I will say a few words about the common aspects of the products

8. Main localization strategies and tools
- Early engagement and evaluations - Translation automation - Auto bug fix - Centralized testing support - Last-minute translation solutions (ALA, Gengo) - Partnerships
Main localization strategies and tools
Our main strategies and tools
Partners: Alpha CRC, Dilato, Gengo

9. Early evaluation

10. AUTOMATION

11. BUG-FIX SCRIPT: Benefits:
Allows QEs to correct bugs in strings, no need to hire international engineer
Easy to update
What is Auto Linguistic Bug Fix?
Background:For some projects, we might face situations with lots of linguistic bugs or hotkey key bugs to fix after UI G11N testing. These bugs are simply string replacement from one translation to another using either WorkBench or changing ALFA resources in P4. In a typical workflow QE submits a bug and pass to linguist for suggestion, or linguist submit a bug directly. The bug then routed back to the i18n engineer or vendor engineer to fix in Workbench or ALFA resources in P4. Auto Linguistic Tool allows the submitter to bypass i18n engineer to fix bugs directly. Once changes are made, the bug is automatically routed back to the assigned QE for regression.
Advantage of this workflow:
Bug Creator can fix simple bugs without vendor/i18n Engineer
Ideal for Hot Keys, shortcuts and translation fixes that do not increase length of strings.
Fix multiple bugs quickly via batch system
Scalable to support more individual to fix bug without adding Workbench accounts overhead. Only Watson/ldap is needed.
Use Watson template format to fill in bug fix details. No need to provide Workbench usage training.
Automation change Watson bug status from ToFix to ToTest once the bug is submitted successfully.
Concept:  The three components to this workflow is Watson, ALF2 Server, and client system (that runs the automation). 
Watson is the front end that specify the string that need to change. We recommend to use the RecordLocator(in ALF2) to specify exact string to change, though this is optional per documentation. With Watson specify the English string, current localized value, and new localized value.  (See details below).
ALF2 project file is already set up to make bug fixes via workbench. This workflow will is not applicable if you fix bugs on P4.
Client System has all the configuration files (Watson, ALF2, and notification) and batch script to automate the project.
Roles:
Adobe i18n Engineers: customize configuration for the project
Linguist: provide translation in watson bug template format and/or submit the Watson bug for defect found.
Vendor QE and IQE: Submit and regress Watson bugs.
Show demo here!
How Auto Linguistic Bug fix works
1. Using MockID and English string
If the <English_win> and <mock_id> tag are listed in the bug, then they used to search the unique string to correct. <loc_win> string is not use for the string search.
2. Using English string
If the <mock_id> is not listed then it is based on <English_win> and <loc_win>. If a match is found then the string is corrected. (Note: In this case if multiple matches found then the same can be handled using MULTIPLE_MATCH flag)
3. Platform variance
Platform variance is being tested. In the future you can tag different platform with _win , _mac , and _unix. For example, <English_mac>, <loc_mac>, and <loc_mac_correct>. More Info to come once this feature is fully tested.

12. GOING FORWARD: - Standardization - Test automation - Consolidate kits - Reduce turnaround time - Further refinement of bug-fix script - Controls to product teams

13. Q&A