|1.5.0||31 October 2019|
Exchange Framework (TIF) makes it easier for developers to build integrations on Journey products in a more efficient, standardised and scalable manner to reduce the ongoing costs of upgrades and maintenance.
Exchange Framework 1.5.0 is a significant release with two major features below.
A standard fluent function base class for integration purposes
This base class provides the most commonly used code for a typical integration fluent function below:
- All initialized variables like logger, svcDef, txn, inputParams, user, appDoc, applicantRole, and fluent function results
- Setup service module
- Standard input parameters injected (recordResponseInTxnProperties, recordResponseInTxnXML)
- Standard milestone events on start and complete
- Standard exception handling and update of server VO and client VO when required
The code pattern in this class has passed hundreds of regression test cases that provide you with a reliable foundation so you can save time and concentrate on your specific project code.
A powerful standard response processor out of the box
Previously, you needed to create a response processor subclass and write code to process the raw response field by field and generate the Server VO and Client VO manually.
From 1.4.0, we started to provide simple annotations, that lets the response processor inject certain values from the raw response into the Server VO automatically.
We go much deeper in 1.5.0, with a lot more auto response processing capabilities, as shown below, to finally provide a fully working response processor out of the box, that saves you time parsing the response manually.
- Client VO auto-processing by annotation
- Properties auto-matching between Client VO and Server VO
- Auto data value mapping
- Turn response directly into Map object in VO and filtering on the result
- JSON string as a single property
- Clear VO properties when Errors Happen
- Default error handling in response processor
With this release, it dramatically reduces the code required in your main fluent function and the code required to manually parse the raw responses. We strongly encourage everyone to upgrade and start using the framework to build your next integration.