6. Testing

Use this Worksheet to manage a test.

6.1. Testing Script

Testing Script

Area	Node	Organization	Role	Action	Expected Result
UI	AAIS	Regulator	Regulator	Log In	Logged in
UI	AAIS	Regulator	Regulator	Create Data Call	Data Call Created in Draft
UI	AAIS	Regulator	Regulator	Create New Draft	New Draft
UI	AAIS	Carrier	Carrier	Like Data Ccall	Like recorded and appears on data call list
UI	Carrier	Carrier	Carrier	Like Data Ccall	Like recorded and appears on data call list
UI	AAIS	Regulator	Regulator	Issue Data Call	Data Call Is in Issued List
UI	AAIS	Regulator	Regulator	View Liking Organizations	List of Orgs that Liked
UI	AAIS	AAIS	Stat-Agent	Update Issued Data Call	Data Call Info Updated
UI	AAIS	AAIS	Stat-Agent	Set Extraction Pattern	Extraction Pattern Visible on Data Call
UI	AAIS	Carrier	Carrier	Download Extraction Pattern	Etraction Pattern downloaded
UI	Carrier	Carrier	Carrier	Download Extraction Pattern	Etraction Pattern downloaded
Extraction Patterns	N/A	N/A	N/A	Create Extraction Pattern	Extraction Pattern Tested
.
Data Load	AAIS	Carrier	Carrier	Load data using the Insurance Data Manager Service
Data Load	Carrier	Carrier	Carrier	Load data using the Insurance Data Manager Service

3. Upload Data

5. Consent to the Data Call

6.2. Assume each of the roles

1. Regulator – regulator

2. State Agent – stat-agent

3. Carrier – carrier

6.3. Execute the functions on the different nodes

1. AAIS Node

2. Analytics Node

3. Carrier Node

6.4. Table of Testing Scenarios

Testing Scenarios

Nodeà		AAIS			Analytics	Carrier
Roleà	Administrator	Regulator	Carrier	Stat-Agent	Stat-Agent	Carrier
Scenario
Login	N/A	Should see the data call list and the option to create a new data call	Should see the data call list but no option to create a data call	Should see the data call list	Should see the data call list	Should see the data call list
Create a Data Call	N/A	Data call should appear in draft list if not issued on creation.	N/A
Issue Data Call	N/A	Data call should appear in issued list	N/A
Upload Data	N/A		Data Should Appear in the Mongo Database			Should see data in the HDS
View Reports	N/A
Create An Extraction Pattern	Extraction pattern is available to be applied to a data call
Publish the Extraction Pattern	Extraction pattern appears in list of available extraction patterns	N/A	N/A	N/A
Update an Extraction Pattern	Extraction pattern is updated in the system	N/A	N/A	N/A
Assign Extraction Pattern	N/A	N/A	N/A	Extraction pattern should be visibly connected to the data call.
Like / Unlike	N/A	N/A	Only available for draft data calls.	N/A
			Number of likes increases or decreases for the data call
View Liking Organizations
View Consenting Organizations		Should see list of consenting carriers
Consent	N/A
Create a User	New user should show up in IBM Cloud list of users for this appid service
Update Chaincode	The new chaincode is used by the network.

6.5. Create a User

The valid roles are “regulator”, “carrier”, “stat-agent”.

For the aais node you will want to create all three kinds.

For the analytics node, only create the stat-agent and regulator roles.

For the carrier node, only create the carrier role.

NOTE: make sure the carrierId matches a carrier id of data that is loaded into the mongodb.

6.5.1. Use the API to create a User

Role: Administrator

1. Open the swagger ui for the utilities and login to get a token

2. Open the swagger ui for the insurance data manager and authorize with the token

3. Open the “app Create User” request.

4. Try it and then fill in the sample data and execute

5. You should now be able to login with that user.

6.6. Login

Role: Any

1. For the different environments, there are different users.

2. Depending on the type of node, there are different kinds of users.

3. Login with the credentials created above.

6.7. Create a Data Call

Role: Regulator

1. Open the data call app (openidl-ui) for the node. (do this on the aais or analytics node)

2. Login as the specified user whose role should be “regulator”.

3. Click on “New Data Call” in the top right.

4. Enter all required information.

5. Click on save as draft or issue.

   1. If saved as draft, confirm it shows in the draft list

   2. If issued, confirm it shows in the issued list

6.8. Issue a Data Call

Role: Regulator

1. Login as a regulator

2. Select a data call from the drafts list

3. Click on issue

4. Confirm that it shows in the issued list now

6.9. Upload Data

Role: Carrier

1. Use the swagger ui for the insurance data manager to load data

2. Confirm that the data gets loaded into the mongo database

6.10. Create an Extraction Pattern

Role: Administrator

Extraction patterns are used to extract data from the harmonized data store and make it available on the analytics node.

A schema is available that documents the extraction pattern json format.

Find it in the openidl-extraction-pattern-developer directory in the openidl-main project in git.

The value of the viewDefinition.map and viewDefinition.reduce elements is javascript and should work as part of a map reduce in mongo. This can be tested using the openidl-extraction-pattern-developer tool. Look into the test cases to see how this can be done.

Create and test the extraction pattern document

1. Create a sample file for the input data.

   1. There are two options for this, use the mapper or copy from mongo

      1. Use the mapper

         1. the openidl-mapper is included in the dependencies

         2. check out the test-mapper.js for how to run it

         3. you can use the generateSampleData.js to create

            1. run ‘make generate_data’

      2. Copy data from a known mongodb

         1. Open mongo client

         2. Go to collection

         3. Select the items and “view as text”

         4. Copy into a text file named inputMongoText.txt in the “process” folder

         5. Run the utility “convertMongoTextToJson.js” npm run convertMongoTextToJson

         6. Grab the valid json from the ouputMongoJson.json in the “processed” folder

   2. Paste it into a file in the test/data directory

2. Create a javascript file with the map and reduce functions you want

3. Create a test that points to that above test data for input – copy from an existing one to get the pattern

4. Require your file with the map and reduce to get those functions to build the extraction pattern

5. Push the extraction pattern to an output file you can use in the follow on steps to publish into openidl

6. Run the tests to make sure your expectations pass

6.11. Update an Extraction Pattern

Follow the same steps to create an extraction pattern except, when publishing use the update existing extraction pattern api instead of the create new.

6.12. Publish the extraction pattern to the openIDL

Role: Administrator

1. Using the data call app api we’ll put the extraction pattern into the system

2. Open the api-docs for the data call app = data-call-app-base-url + /api-docs/ (see below to get the base url)

3. Authorize as defined in 11.4.7.5

4. Authorize with a token from the postman request for the token for the resource group

5. Open the create data call service in the swagger screen (if updating existing, use the update api instead)

6. Click on try it out

7. Paste the text of the extraction pattern into the example value

8. Click on execute

9. You should receive an ok result with success true

   1. If there are errors then look into the logs for the data call app, it should tell you why the endorsement failed, usually it is something wrong with the format of the extraction pattern

6.13. Assign the extraction pattern to a data call

Role: Stat-Agent

1. log into the application as a stat agent

2. open the data call

3. set the extraction pattern to what you want

6.14. Like or Unlike a Data Call

Role: Carrier

1. log into the application as a carrier

2. open a draft data call

3. click on the like data call

4. go back to the list of draft data calls

5. the data call should have one more like (you may need to refresh the page)

6. go back into the data call

7. unlike the data call

8. go back to the list

9. the data call should have one less like (you may need to refresh the page)

6.15. View Organizations that Have Liked a Data Call

You may need to log out of the application and log back in then go to the draft data call to see the link appear.

Role: Carrier

1. Log in to the application

2. Open a draft data call

3. Next to the likes, click the “View Organizations” link.

4. A list of organizations appears.

6.16. View Organizations that Have Consented to a Data Call

Role: Regulator

1. Log into the application

2. Open an issued data call

3. Click on the “View Carriers” link next to the Carrier Consents count.

6.17. Consent to the data call

Role: Carrier

1. Log into the application

2. Open an issued data call

3. Click on “Consent to the Report”

4. The “Consent Recorded:” field should update with current date and time.

5. Go back to the list of data calls, this one should have another consent.

6. Check the mongo database for a new collection created by the extraction pattern execution. It will be for the specific carrier with a generated suffix identifier.

7. Confirm the analytics node gets the data as expected

8. Something should show up in the aws s3 bucket

   1. The s3 bucket is openIDL-analytics

   2. There could multiple files based on the extraction pattern

   3. Make sure that there is the appropriate data in the files again based on the extraction pattern

6.18. Update Chaincode

From time to time, the chaincode needs to change. To deploy to the node, run the toolchain after checking into

All nodes should be updated together to make sure they all have the same chaincode. Run each.

You may need to change the version in the configuration of the BUILD stage.

6.19. The actual process should be

consent at date x

data call is at date y

load data at time of y

is there some kind of window of time to allow data to be captured

like in draft

consent

analytics node should be looking through the data calls to find the finished data calls and firing the extraction at that time

each carrier node polls to know when to run the extraction pattern

the movement of data into s3 should not happen

6.20. Testing Utilities

A best practice is never to commit credentials to git. To get around this for our test environments, we keep the credentials in a box folder. openIDL_environments. Make a sub folder for your environment and node in the same way you named the resource group.

6.20.1. Data Call Helpers

TODO: Verify

In the course of testing the application, many elements need to be repeated many times. This can and should be done using the UI to verify that the UI is working correctly. To facilitate rapid testing of the api’s however, it is advantageous to be able to execute the functionality from a command line. The data-call-app has some testing utilities to create and consent to data calls.

Use one of the following:

node test/api/api-create-data-call.js

node test/api/api-consent-to-data-call.js

node test/api/api-create-and-consent-to-data-call.js

Make sure to update the data call information before running these.

6.20.2. Viewing the MongoDB for testing purposes

The mongo database is available in the cloud

See section useDeploy MongoDB for details on connecting to mongo.

6.20.3. Getting the URL for the application

TODO ??

6.20.4. Determining the base URL for an Application

TODO ??

6.20.5. Getting Credentials for APIs

TODO ??

6.20.6. Debugging a Consent Call

Trying to follow the path of the consent operation is a complex undertaking. The flow is something like this:

1. Carrier consents to data call

2. The UI calls the createConsent service in the data-call-app

3. Data call app submits the transaction “CreateConsent” to the ledger api

4. The extraction pattern is executed by the data call processor and the mongo db is updated with a collection that represents the results of the extraction pattern

7. App Debugging

7.1. Checking the logs for the different components

The logs for the different pods can be accessed through kubectl.

Setup aws and configure your eks command to point to the specific cluster:

something like:

aws eks update-kubeconfig –region us-east-1 –name aais-dev-blk-cluster

Then you can use the usual kubectl commands to get the pods:

kubectl get ns

Then you can get the pods in a namespace

kubectl -n aais-net get po

Then you can get the logs for one of the pods and follow it too.

kubectl -n aais-net logs peer0-0 -c peer0

7.2. DNS Troubleshooting

If your route53 is incorrect because the domain and subdomain are incorrect, then follow these steps:

1. Update input file with .com

2. Delete the hosted zones from Route53 that was created including the records and the zones

   1. Delete all but the NS and SOA records, then

   2. Delete the hosted zone

3. Rerun the pipeline AWS_Resources

4. Rerun the pipeline for K8s_Resources

If you get an access denied error in the log for the data-call-app, rerun the register users baf action.

Alternately, it could be an error in the config file for the channel name - should be defaultchannel and anal-<organizationName> where the organizationName must be 4 or less characters.