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

- 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

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

AdobeCreativeSDKFoundation CreativeSDKFoundationAssets CreativeSDKFoundationAuth AdobeSDKDevice AdobeCreativeSDKBehance AdobeCreativeSDKColor CreativeSDKImage

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

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!

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

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

Early evaluation

AUTOMATION

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 email 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.

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

Q&A