//  Copyright 2012 conversionworks.org
//
//  Master Branches
//    iOS code: https://github.com/drawbridge/CWorks
//
//  Contributors:
//      https://github.com/anupamtulsyan (initiator & iOS code)

Synopsis: an open source project to provide a conversion tracking 
          solution for iOS without the use of Unique Device Identifier (UDID)

Usage:
 #include "CWorks.h"
  
  //record click
  [CWorks recordClick:@"testapp" forAdNetwork:@"drawbridge" uniqueId:@"testid"];
  
  //record Impression
  [CWorks recordImpression:@"testapp" forAdNetwork:@"drawbridge" uniqueId:@"testid"];

  //get list of clicks. All clicks for this app are deleted once accessed.
  NSDictionary * dict = [CWorks getClicks:@"testapp"];

  //get list of Impressions. All impressions for this app are deleted once accessed.
  NSDictionary * dict = [CWorks getImpressions:@"testapp"];

  Check for nil dictionary objects when getting the records. Data returned by get functions 
  is in the following format,
  
  type.networkName.uniqueId  ==> timestamp (UTC in milliseconds)
  
  where type is the either "i" for impression or "c" for click. network name and unique id 
  is the same as passed by the ad network.
  
  
  Default number of impressions or clicks stored in the pasteboard for a given app is 50. 
  Please change the parameter kMaxPasteBoardItems present in CWorks.m to suitable number 
  for your implementation if needed.
  
  
Context:

Conversion tracking is a crucial component of any performance based advertising solution. 
Mobile ad networks, supply and demand side platforms have traditionally adopted a conversion 
tracking approach based on the UDID on iOS. With Apple recently taking a position against 
the use of the UDID and deprecating access to the same, there is a need for an innovative, 
privacy friendly solution. 

Additionally developers who use multiple channels for advertising and solving their user 
acquisition needs, stand to benefit tremendously from a transparent, open and privacy 
friendly standard for conversion tracking. This open source initiative addresses a real 
need in the ecosystem around a fair standard for attributing conversions to the rightful 
driver, obviating duplicate claims. 

As proprietary solutions around device identification emerge it could lead to fragmentation 
and hence creating challenges for a unified conversion tracking solution. This project is 
an open source initiative to solve this problem for many developers and continue to make it 
a thriving and efficient ecosystem. 


Credits: 

Yann Lechelle, OpenUDID project and many other developers for laying the seeds of creative 
solutions for this problem.