A unit test is method that calls functions or piece of codes from your source code with some inputs and then validates if the output is the one that you want to expect. Thus, these tests validates if the result is the one expected. The method or function to be tested is known as System under test (SUT).
These tests are automated in the continuous integration system (CircleCI) and are executed in each new version of the software.
Here you have the technologies used in this project
- ASK CLI - Install and configure ASK CLI
- CircleCI Account - Sign up here
- Node.js v10.x
- Visual Studio Code
We are going to use the npm package ask-sdk-test which is the newest version of the npm package alexa-skill-test-framework.
This new version is built in TypeScript and is really easy to use in both JavaScript and TypeScript Alexa Skills.
This framework makes it easy to create full-coverage black box tests for an Alexa skill using Mocha.
You can install ask-sdk-test using npm. --save-dev is used to save the package for development purpose. Example: linters, minification.
npm install ask-sdk-test --save-devThis framework uses the npm package mocha to run the tests. So we need to install it as well:
npm install mocha chai --save-dev Once we have the test framework installed and its dependencies now we have to write some unit tests.
You can find all the tests in the helloworld-tests.js in lambda/cutom/test folder.
We are going to explain step-by-step this file.
First, the initialization of the test framework and the i18n library is required to write some unit tests:
// include the testing framework
const test = require('ask-sdk-test');
const skillHandler = require('../src/index.js').handler;
// i18n strings for all supported locales
const languageStrings = require('../src/utilities/languageStrings.js');
const i18n = require('i18next');
// initialize the testing framework
const skillSettings = {
appId: 'amzn1.ask.skill.00000000-0000-0000-0000-000000000000',
userId: 'amzn1.ask.account.VOID',
deviceId: 'amzn1.ask.device.VOID',
locale: 'es-ES',
};
i18n.init({
lng: skillSettings.locale,
resources: languageStrings,
});
const alexaTest = new test.AlexaTest(skillHandler, skillSettings);With the lines above now we can start writing unit tests as easy as this:
describe('Hello World Skill', function() {
// tests the behavior of the skill's LaunchRequest
describe('LaunchRequest', function() {
alexaTest.test([
{
request: new test.LaunchRequestBuilder(skillSettings).build(),
saysLike: i18n.t('WELCOME_MSG'), repromptsNothing: false, shouldEndSession: false,
},
]);
});
// tests the behavior of the skill's HelloWorldIntent
describe('HelloWorldIntent', function() {
alexaTest.test([
{
request: new test.IntentRequestBuilder(skillSettings, 'HelloWorldIntent').build(),
saysLike: i18n.t('HELLO_MSG'), repromptsNothing: true, shouldEndSession: true,
},
]);
});
// tests the behavior of the skill's Help with like operator
describe('AMAZON.HelpIntent', function() {
alexaTest.test([
{
request: new test.IntentRequestBuilder(skillSettings, 'AMAZON.HelpIntent').build(),
saysLike: i18n.t('HELP_MSG'), repromptsNothing: false, shouldEndSession: false,
},
]);
});
describe('AMAZON.CancelIntent and AMAZON.CancelIntent', function(){
alexaTest.test([
{ request: new test.IntentRequestBuilder(skillSettings, 'AMAZON.CancelIntent').build(),
says: i18n.t('GOODBYE_MSG'), shouldEndSession: true },
{ request: new test.IntentRequestBuilder(skillSettings, 'AMAZON.CancelIntent').build(),
says: i18n.t('GOODBYE_MSG'), shouldEndSession: true },
]);
});
});Once we have everything configured, we have to set up the reports we are going to use to check the output of the unit tests.
The first report we need to set up is the JUnit report.
We need to install this output format of the report:
npm install mocha-junit-reporter --save-dev This report will generate a .xml file as output that CircleCI is going to use to print the lint results:
We are going to move one step forward. We want to know a little bit more about our unit tests results in every pipeline execution.
This is why we are going to add the mochawesome npm package to generate a beautiful HTML report with more information rather than the above explained:
npm install mochawesome --save-devThis is how this report looks like:
Finally, in order to generate two reports with just one command we will install another npm package: mocha-multi-reporters
npm install mocha-multi-reporters --save-devThen we have to configure this npm package to specify the two reporters we are going to run ant its configuration.
The configuration file is mocha.json file in lambda/custom folder:
{
"reporterEnabled": "mocha-junit-reporter, mochawesome",
"mochaJunitReporterReporterOptions": {
"mochaFile": "reports/mocha/test-results.xml"
}
} The JUnit report will be stored in lambda/custom/reports/mocha/ folder and the HTML one will be stored in lambda/custom/mochawesome-report.
Now it is time to integrate it into our package.json to use it in our pipeline with npm run commands!
So, in this file we are going to add the following commands in the script json node:
test: this command will execute the unit tests and generates the reports:mocha --reporter mocha-multi-reporters --reporter-options configFile=mocha.json
Everything is fully installed, configured and integrated, let's add it to our pipeline!
This job will execute the following tasks:
- Restore the code that we have downloaded in the previous step in
/home/node/projectfolder - Run
npm run testto execute the unit tests. - Store the JUnit report as CircleCi test artifacts.
- Store the HTML report as an CircleCi artifact of this job.
- Persist again the code that we will reuse in the next job
test:
executor: ask-executor
steps:
- attach_workspace:
at: /home/node/
- run: cd lambda/custom && npm run test
- store_test_results:
path: lambda/custom/reports/mocha/
- store_artifacts:
path: ./lambda/custom/mochawesome-report/
- persist_to_workspace:
root: /home/node/
paths:
- project- DevOps Wikipedia - Wikipedia reference
- Official Alexa SDK Test Framework Documentation - Alexa SDK Test Framework Documentation
- Official CircleCI Documentation - Official CircleCI Documentation
The main goal of unit tests is to detect errors within individual software components. The idea is to ensure the accuracy of the code throughout the development process. It is necessary to write unit tests constantly.
I hope this example project is useful to you.
You can write unit tests with Bespoken as well. See documentation here
That's all folks!
Happy coding!