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Generate single microflow (unit) tests

Thursday October 13, 2022
Markus Travaille, Rolf Bolt

In our latest blog we wrote about “why single microflow testing is not taking off in Mendix teams“. We identified three test adoption blockers that can be traced back to: the size of the investment, the uncertain investment returns and the lack of progress information.

Today we are presenting how a new MTA feature “generate single microflow (unit) tests” is enhancing the test configuration speed reducing the first of the three defined adoption blockers. We will finish this blog with a little sneak-peek about the direction of our innovations that will help to solve the other test adoption blockers as well.

Beyond Direct Model Testing; test generation

In the past decade, we have seen that development cycles are more and more focused on adding business value in the shortest amount of time possible. Low-code supports that focus by shifting from technical craftsmanship to creating a model that captures business logic and requirements. Based on this model the code is generated, which produces a working app.

As we mentioned earlier, testing and test automation has not made the same shift in focus. Test automation is often relying on scarce expertise, manual processes and a lot of maintenance. We decided to change that perspective and introduced ‘Direct Model Testing‘ last year. This technology utilizes the existing app model to create test scripts instead of leaning on testing expertise to build them from scratch.

Direct model testing saves a lot of time when creating and maintaining test scripts. But we want to enhance the concept with generation. Generating test scripts will further reduce the cost of creating and maintaining tests, leading to a better return on test investments.

Our first innovation in MTA 1.6 was to add a recorder which you can generate tests with, by recording them (see Menditect recorder). This empowers the creation of process tests but is hardly speeding up the creation of single microflow tests (unit tests).

That has changed with MTA version 1.8. In this version we added test generation for single microflows.

Current process – manual setup of teststeps

Let’s have a look at which actions are needed to configure a single microflow test step. Schematically the process looks like this:create single microflow test manual

Create object input parameter(s):

  • Configure optional test steps that creates or retrieves objects based on the existing Mendix model.

Alter object input parameter value(s)

  • Set the desired object attribute values.

Select microflow for execution

  • Select the microflow from the Mendix Model.
  • Set the literal input parameter values and select object input parameters.

Create assert(s)

  • Configure optional retrieval of output objects.
  • Configure assert(s) on output values.
  • Setting expected results.

Add rollback action

  • Add an optional rollback action to keep your test database clean.

These actions require a lot of clicks and configuration actions, especially when your test scripts are getting large and you have to deal with microflows with a lot of input parameters.

New process – generate single microflow (unit) tests

In our 1.8 release (september 2022) we save a considerable amount of time by letting MTA create and fill the input parameters automatically (light blue steps). Configuring a single microflow test is now requiring three manual steps instead of five:Generate single microflow (unit) tests - generated

Select microflow for execution

  • You start with selecting a microflow instead of selecting the input parameters.

Generate object input parameter(s)

  • MTA generates the microflow object input parameters automatically and adds these as precursor steps to the test script. This saves considerable time because no upfront analysis is required to find out which parameters are requested by the microflow.

Generate input parameter values

The generator generates for every microflow parameter randomized input values. The following randomization is applied:

  • Objects: a copy of a random object from the database of your choosing is generated.
  • Lists: same as object, so the list contains only one object.
  • Literals: Boolean and enums: a random allowed value. Integers, longs and decimals: a random negative or positive number. String: the word ‘random’. Date: the current date-time.

Alter input parameter value(s)

  • Review input parameter values and change some of them if necessary.

Create asserts

  • nothing changed

Reduce the setup of a single microflow test from 47 clicks to 3

With the new process of MTA 1.8 we were able to reduce the number of clicks to set up a single microflow test considerably when MTA generates a single microflow (unit) test. In the video below we show how this works for a unit test that we have frequently used in our demo’s.

If your unit test has more parameters the savings in time can be even larger than shown in this video

 

Conclusion and outlook

We have promised to work on removing key blockers for single microflow testing. Adding the “generate single microflow (unit) tests” option in MTA helps to solve the first of the three blockers; it lowers the test investment to the point that test automation is more profitable. Second, it makes test automation much more intuitive, making it easier for the Mendix developer/tester to create tests.

However, we are not done yet. In the future, we will enhance single microflow test generation by assisting the tester to generate test data that will be retrieved by the microflow under test or one of its sub-microflows (called “generate implicit input parameters”). We even plan to add data variation on test case level and generate data variation based on database content.

In our previous blog we wrote about the need for ‘early testing’. We are going to support that and make MTA capable of testing the application on the developer’s computer. The application can then be tested without the need of deploying the app first (shift left testing).

We do have more innovative ideas around assert generation, test coverage measurement and supporting the test automator with intelligent advice. Our final goal is to make testing so easy that it is a no-brainer to configure tests.

Markus Travaille

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