What is the difference between functional test and end-to-end test?
Techopedia says that end-to-end test is
a methodology used to test whether the flow of
an application is performing as designed from start to finish. The
purpose of carrying out end-to-end tests is to identify system
dependencies and to ensure that the right information is passed
between various system components and systems.
Techopedia also says the following about functional test:
Functional testing is a software testing process used within software
development in which software is tested to ensure that it conforms
with all requirements. Functional testing is a way of checking
software to ensure that it has all the required functionality that's
specified within its functional requirements.
After reading the above two paragraphs, I'm still confused about the difference between them.
I have a node.js application which accepts requests, then parses the request, then sends the parsed data to a Database.
requests parse requests and send data to the database
Client ---------> node.js app --------------------------------------------> Database
How can I write end-to-end test and functional test for the node.js app I mentioned?
I think in both types of the tests, I should treat the node.js app as a black box. And send requests to it. Then check if the output of the black box is correct or not.
It seems that in my case, there's no difference between functional test and end-to-end test.
As I understand it, the biggest difference between the two is that an end-to-end test requires the test to setup the system components as they are in production. Real database, services, queues, etc. The reason for this is to see that your system is wired correctly (database connections, configuration and such).
A functional test can setup the system with in-memory implementations of your application ports, which would make the test run faster and perhaps allow tests to run in parallel (in some cases). The only thing the test cares about is that a feature works as expected. This can reduce the overhead of setting up certain tests, since preparing 3rd party systems with data can be difficult or time consuming.
I think the definitions of functional and end to end testing could vary based on the context of your project. I have seen different people use these terms to describe different things. That being said, usually this is what the 2 terms mean-
Functional testing - This refers to testing the functionality of system based on the requirements. This usually focuses on different requirements of the system and ensure it is working properly. For example - Logging into an application - could be one requirement and then a person could test this functionality manually or in an automated way. Similarly, adding a product to the cart could be one functionality, then, able to make a payment to purchase a product could be a functionality.
End to end testing - This refers to testing the system based on end to end user flows, instead of testing the system has separate components like in unit testing or story level testing. For example - Logging into the application, then adding a product to the shopping cart, then going to the check out screen and then placing an order and then logging out of the application could be one user flow.
What we follow is slightly different and of course difference in just how your team treats each of them. for further clarity,
Functional Test : Tests a feature say login, verify from database if login data is correct, verify if intended event received, or send to a message bus or any external activity in a Prod like environment like staging environment. You test a particular functionality in a real environment.
End to End testing : Test complete feature like, login to app, view product on view page, select product, checkout and do payment. This could cover multiple microservices as well, or maybe multiple teams. If this flow breaks, we can pin point which of the functional tests failed.
Integration Test: Test integration between multiple components, from a wide spectrum of multiple classes to multiple system. Like can UI connect to some external login service, can backend connect to database. If a functional test breaks, we can watch which Int Test failed and so on with unit test.
Related
I have a few Nifi process groups which I want to run integration tests on before promoting to production. The issue is that I can't seem to find any documentation on how to do so.
Data Provenance seems like a promising tool to accomplish what I want, however, over the course of the flowfile's lifecycle, data is published to/from kafka or the file system. As a result, the flowfile UUID changes so I cannot query for it using the nifi-api.
Additionally, I know that Nifi offers a TestRunner library to run tests, however, this seems to only be for processors/processor groups generated via code and not the UI.
Does anyone know of a tool, framework, or pattern for integration and unit testing nifi process groups. Ideally this would be a solution where you can programatically compare input/output of the processor/processor group without modifying the existing workflow.
With the introduction of the Apache NiFi Registry, we have seen users promote flows from a development/sandbox environment to a test/QE environment where there are existing "test harness" flows surrounding the "flow under test" so that they can send repeatable and deterministic (or an anonymized sample of real production data) through the flow and compare the results to an expected value.
As you point out, there is a TestRunner class and a whole testing framework provided for unit tests. While it can be difficult to manually translate a UI-constructed flow to the programmatic construction, you could also create something like a translator to accept a flow template or flow.xml.gz file and convert it into something processable by the test framework.
Maybe plumber will help you with flow testing.
We also wanted to test whole NiFi flows, not just single processor, so we created this library and decided to open-source it.
Simple example in Scala:
// read flow previously exported from NiFi
val template = TemplateDeserializer.deserialize(this.getClass.getClassLoader.getResourceAsStream("exported-flow.xml"))
val flow = NifiTemplateFlowFactory(template).create()
// enqueue some data to any processor
flow.enqueueByName("csv row,12,another value,true", "CsvParserProcessor")
// run entire flow once
flow.run(1)
// get the results from any processor
val records = flow.resultsFromProcessorRelation("LastProcessorInFlow","successRelation")
records should have size 1
This library is still under development so improvements and ideas are welcomed! :)
Can you have automated regression/integration tests for Azure Logic Apps?
And if you can, how? ... especially in the context of CI/CD builds and deployments
... and if you can't, why not!!
There isn't any out-of-the-box tooling yet to provide automated testing of Azure Logic Apps. We have a few customers who have followed one of the following patterns. There is also this article that goes into detail on how to create a Logic App deployment template:
After deployment (using a release management tool like Visual Studio Release Management), a series of unit tests are run (writtin in something like C#) to test the Logic App.
Since a logic app could have any kind of trigger (on queue item, on HTTP request), the code usually performs the action and asserts the result.
A logic app in the resource group that can run a series of basic tests in a workflow. This one requires a bit more chewing on, but idea being you have a workflow that makes use of connectors or "calling nested apps" to perform basic validation tests (ensure connections are active, etc.)
It's something we have had discussions on from time-to-time, but would love to know if you have any thoughts on what types of tooling/configuration you'd want to configure for an app (remember that some apps "trigger" on something like a message in a queue or a file in FTP).
I would like to share one of the approach for LogicApp testing that my team has followed.
First level of validation is the ARM template deployment status (ProvisioningState) which should not have any errors.
After that we have developed test automation using the logic app sdk which does the following
Get auth token.
Execute a specific logic app trigger with a synthetic transaction.
Waits till the execution is completed.
Gets logic app & its action status (succeed, failed or skipped), validates it as per the expected scenario.
Gets the outputs from each action execution, validates them against an expected scenario.
Repeat above steps for all the various cases that logic app might go through.
Hook this all-in CI/CD :)
Deployed an LA, ran a synthetic transaction & validated the results.
Hope this helps.
I have a web application which needs to be tested in multiple browsers in multiple environments (i.e. Chrome, Firefox, and Internet Explorer in both Windows and Linux* (*with the obvious exception of Internet Explorer)).
Tests have been written in Java using JBehave, Selenium, and SerenityBDD (Thucydides)). These tests exercise an underlying REST API, testing if objects may be successfully created and deleted using the UI.
I am using Selenium Grid, and would like to run the tests on parallel nodes; however, the concern is that as the tests exercise an underlying REST API, there could be conflicts.
Is it possible to pass in parameters to the tests as a parameter within the Jenkins job configuration which runs the tests, so that there is a slight difference in the tests dependent on the node in which they are executing? (e.g. An object named 'MYOBJECT-CHROME' is created on Chrome, versus an object named 'MYOBJECT-FIREFOX' on Firefox, meaning any REST API conflicts can be avoided?)
If the software under test(SUT) allows multithread REST API requests there is no need for you worry about
meaning any conflicts can be avoided?
The tests concurrent requests should be set up as fixtures, meaning every atomic test should set/tear down the required for it test data or return the software under test's(SUT) state. A good candidate here is a Prebuilt fixture. It'll allow you to add it as a step in Jenkins and can reduce the overhead of creating all those test objects.
If you still need to parameterize the build, you can use your suite #tags from the BDD to define which set of tests will be executed.
I was tasked with creating a health check for our production site. It is a .NET MVC web application. There are a lot of dependencies and therefore points of failure e.g. a document repository, Java Web services, Site Minder policy server etc.
Management wants us to be the first to know if ever any point fails. Currently we are playing catch up if a problem arises, because it is the the client that informs us. I have written a suite of simple Selenium WebDriver based integration tests that test the sign in and a few light operations e.g. retrieving documents via the document api. I am happy with the result but need to be able to run them on a loop and notify IT when any fails.
We have a TFS build server but I'm not sure if it is the right tool for the job. I don't want to continuously build the tests, just run them. Also it looks like I can't define a build schedule more frequently than on a daily basis.
I would appreciate any ideas on how best achieve this. Thanks in advance
What you want to do is called a suite of "Smoke Tests". Smoke Tests are basically very short and sweet, independent tests that test various pieces of the app to make sure it's production ready, just as you say.
I am unfamiliar with TFS, but I'm sure the information I can provide you will be useful, and transferrable.
When you say "I don't want to build the tests, just run them." Any CI that you use, NEEDS to build them TO run them. Basically "building" will equate to "compiling". In order for your CI to actually run the tests, it needs to compile.
As far as running them, If the TFS build system has any use whatsoever, it will have a periodic build option. In Jenkins, I can specify a Cron time to run. For example:
0 0 * * *
means "run at 00:00 every day (midnight)"
or,
30 5 * 1-5 *
which means, "run at 5:30 every week day"
Since you are making Smoke Tests, it's important to remember to keep them short and sweet. Smoke tests should test one thing at a time. for example:
testLogin()
testLogout()
testAddSomething()
testRemoveSomething()
A web application health check is a very important feature. The use of smoke tests can be very useful in working out if your website is running or not and these can be automated to run at intervals to give you a notification that there is something wrong with your site, preferable before the customer notices.
However where smoke tests fail is that they only tell you that the website does not work, it does not tell you why. That is because you are making external calls as the client would, you cannot see the internals of the application. I.E is it the database that is down, is a network issue, disk space, a remote endpoint is not functioning correctly.
Now some of these things should be identifiable from other monitoring and you should definitely have an error log but sometimes you want to hear it from the horses mouth and the best thing that can tell you how you application is behaving is your application itself. That is why a number of applications have a baked in health check that can be called on demand.
Health Check as a Service
The health check services I have implemented in the past are all very similar and they do the following:
Expose an endpoint that can be called on demand, i.e /api/healthcheck. Normally this is private and is not accessible externally.
It returns a Json response containing:
the overall state
the host that returned the result (if behind a load balancer)
The application version
A set of sub system states (these will indicate which component is not performing)
The service should be resilient, any exception thrown whilst checking should still end with a health check result being returned.
Some sort of aggregate that can present a number of health check endpoints into one view
Here is one I made earlier
After doing this a number of times I have started a library to take out the main wire up of the health check and exposing it as a service. Feel free to use as an example or use the nuget packages.
https://github.com/bronumski/HealthNet
https://www.nuget.org/packages/HealthNet.WebApi
https://www.nuget.org/packages/HealthNet.Owin
https://www.nuget.org/packages/HealthNet.Nancy
How can I test error messages on MVVMCross?
I'm using ReportError method found on this sample on a Portable Class Library project:
http://slodge.blogspot.com.br/2012/05/one-pattern-for-error-handling-in.html
What are you actually looking to test?
If you are looking to unit test the 'hub' that listens for and republishes errors, then you should be able to do that easily - just create an nunit test and one or more mock subscribers - then you can test sending one or more messages.
If you are looking to test some of your services or view models to check that they correctly report errors, then create unit test for them with mocks which simulate the error conditions - in the test, Assert that the errors are correctly reported.
If you are looking to just manually trigger the ui as part of development, then either find some way to reliably trigger an error (e.g. providing an incorrect password or switching the phone to flight mode) or consider adding a debug ui to your app with buttons to trigger mock errors.
If you are looking for integration or acceptance level testing, then either write manual test steps to trigger errors - or consider automated solutions like Frank, Calabash, Telerik ui testing or the excellent Windows Phone Test Framework (http://m.youtube.com/watch?v=2JkJfHZDd2g) - although I might be biased on the last one
As an update on the error reporting mechanism itself, I have now moved in some of my apps to the more general messenger plugin for this type of reporting. But other apps still use the old mechanism.