Why there’s no such thing as codeless automation

In today’s blog post – which, again, is really nothing more than a thinly veiled rant – I’d like to cover something that’s been covered before, just not by me: codeless test automation and why I think there isn’t and should not be such a thing.

I’ve seen numerous ‘solution’ vendors advertise their products as ‘codeless’, implying that everybody in the team will be able to create, run and maintain automated tests, without having to, well, write code. I’ve got a number of problems with selling test automation in this way.

It’s not codeless. It’s hiding code.
The first gripe I have with ‘codeless’ automation is a semantic one. These solutions aren’t codeless at all. They simply hide the code that runs the test from plain sight. There are no monkeys in the solution that magically execute the instructions that make up a test. No, those instructions are translated into actual code by the solution, then executed. As a user of such a solution, you’re still coding (i.e., writing instructions in a manner that can be interpreted by a machine), just in a different syntax. That’s not codeless.

While it might be empowering, it’s also limiting.
Sure, using codeless tools might potentially lead to more people contributing to writing automated tests (although from my experience, that’s hardly how it’s going to be in the end). The downside is: it’s also limiting the power of the automated tests. As I said above, the ‘codeless’ solution is usually nothing more than an abstraction layer on top of the test automation code. And with abstraction comes loss of detail. In this case, this might be loss of access to features of the underlying code. For example, if you’re using a codeless abstraction on top of Selenium, you might lose access to specific waiting, synchronization or error handling mechanisms (which are among the exact things that makes Selenium so powerful).

It might also be loss of access to logging, debugging or other types of root cause analysis tools, which in turn leads to shallower feedback in case something goes wrong. While the solution might show you that something has gone wrong, it loses detail on where things went wrong and what caused the failure. Not something I like.

Finally, it might also limit access to hooks in the application, or limit you to a specific type of automated tests. If such a solution makes it potentially easier to write automated tests on the user interface level, for example, there’s significant risk that all tests will be written at that level, even though that might not be the most efficient approach in the first place. If all you’ve got is a hammer…

It’s doing nothing for the hard problems in creating maintainable automation.
Let’s face it: while writing code might seem hard to people that haven’t done it before, it actually isn’t that difficult once you’ve had a couple of basic programming classes, or followed a course or two on Codecademy. What is hard is writing good, readable, maintainable code. Applying SOLID and DRY principles. Structuring your tests. Testing the right thing at the right level. Creating a solid test data and test environment strategy. Those things are hard. And codeless test automation does nothing for those problems. As I tried to make clear in the previous paragraphs, it’ll often make it even harder to solve those problems effectively.

I’m all for creating solutions that make it easier to write, run and maintain automation. I hate people selling solutions as something they’re not. Codeless test automation is not going to solve your test automation problems. People that know

  • how to decide what good automation is
  • how to write that automation, and
  • how to pick the tools that will help them achieve the goals of the team and organization

will.

Why I think unit testing is the basis of any solid automation strategy

In a recent blog post I talked about why and how I still use the test automation pyramid as a model to talk about different levels of test automation and how to combine them into an automation strategy that fits your needs. In this blog post I’d like to talk about the basis of the pyramid a little more: unit tests and unit testing. There’s a reason -or better, there are a number of reasons- why unit testing forms the basis of any solid automation strategy, and why it’s depicted as the broadest layer in the pyramid.

Unit tests are fast
Even though end-to-end testing using tools like Selenium is the first thing a lot of people think about when they hear the term ‘test automation’, Selenium tests are actually the hardest and most time-intensive to write, run and maintain. Unit tests, on the other hand, can be written fast, both in absolute time it takes to write unit test code as well as relative to the progress of the software development process. A very good example of the latter is the practice of Test Driven Development (TDD), where tests are written before the actual production code is created.

Unit tests are also fast to run. Their run time is typically in the milliseconds range, where integration and end-to-end tests take seconds or even minutes, depending on your test and their scope. This means that a solid set of unit tests will give you feedback on specific aspects of your application quality much faster than those other types of tests. I stressed ‘specific aspects’, because while unit tests can cover ground in relatively little time, there’s only so much they can do. As goes for automation as a whole.

Unit tests require (and enforce) code testability
Any developer can tell you that the better structured code is, the easier it is to isolate specific classes and methods and write unit tests for them, mocking away all dependencies that method or class requires. This is referred to as highly testable code. I’ve worked in projects where people were stuck with badly testable code and have seen the consequences. I’ve facilitated two day test automation hackathon where the end goal was to write a single unit test and integrate it into the Continuous Integration pipeline. Writing the test took ten minutes. Untangling the existing code so that the unit test could be written? Two days MINUS ten minutes.

This is where practices like TDD can help. When you’ve got your tests in place before the production code that lets the tests pass is written, the risk of that production code becoming untestable spaghetti code is far lower. And having testable code is a massive help with the next reason why unit testing should be the basis of your automation efforts.

Unit tests prevent outside in test automation (hopefully)
If you’re code is testable, it means that it’s far easier to write unit tests for it. Which in turn means that the likelihood that unit tests are actually written increases as well. And where unit tests are written consistently and visibly, the risk that everything and its mother it tested through the user interface (a phenomenon I’ve seen referred to as ‘outside-in test automation’) is far less high. Just writing lots of unit tests is not enough, though, their scope, intent and coverage should be clear to the team as well (so, testers, get involved!).

Unit tests are a safety net for code refactoring
Let’s face it: your production code isn’t going to live unchanged forever (although I’ve heard about lines of COBOL that are busy defying this). Changes to the application, renewed libraries or insights, all of these will in time be reason to refactor your existing code to improve effectivity, readability, maintainability or just to keep things running. This is where a decent set of unit tests helps a lot, since they can be used as a safety net that can give you feedback about the consequences of your refactoring efforts on overall application functionality. And even more importantly, they do this quickly. Developers are humans, and will move on to different tasks if they need to wait hours for feedback. With unit tests, that feedback arrives in seconds, keeping them and you both focused and on the right track.

In the end, unit tests can, will and need not replace integration and end-to-end tests, of course. There’s a reason all of them are featured in the test automation pyramid. But when you’re trying to create or improve your test automation strategy, I’d advise you to start with the basis and get your unit testing in place.

By the way, for those of you reading this on the publication date, I’d like to mention that I’ll be co-hosting a webinar with the folks at Testim, where I’ll be talking about the importance of unit testing, as well as much more with regards to test automation strategy. I hope to see you there! If you’re reading this at a later date, I’ll add a link to the recording as soon as it’s available.

An experiment in creating better tool-centered automation training

Last week, I delivered the second part of a two-evening API testing training at my former employer. They contacted me a while ago to see if I could help them in offering test automation training for their employees, as well as for their clients and other contacts. When I was still working with them, I used to deliver automation training as well, and it felt really great to be asked back, even though I have left them almost three years ago now.

But that’s not what this post is about.

This API testing training was in some ways an experiment I have wanted to conduct for a while now. I see a lot of individuals and organizations offering automation training, and most of it is specific to one single tool. In itself, this isn’t inherently a bad thing, but I’ve got one big problem with a lot of these tool-centered courses: instead of teaching you how to create a sound automation approach around one or more tools, they simply go through the most important features of a single tool and teach the participants some (sometimes useful) tricks. I know. I’ve delivered those courses in the past as well. If you’re a tool vendor / creator, I can understand why you would want to do that. But I think there’s more to good automation education than teaching you all the ins and outs of a specific tool. Let’s call them the 3 C’s:

  • Context – A tool is often only useful in a specific context. This context includes the skills of the people that will use the tool, the development and delivery process that the tool is to be made part of, and much more. Without context, it’s very hard to decide if a specific tool is the right one for the job.
  • Competition – For nearly all tools out there, there’s at least one competitor on the market (but often much more) that can be used to complete the same task. It is therefore essential for good training to introduce more than one option, have the participants get some hands on experience with all of them and let them decide what would work best for their tasks and team.
  • Cutting the crap – Tool-specific training might give the idea that the tool the participants are being trained in is the best thing since sliced bread. Which in turn leads people to try and automate anything and everything with a single tool. Which in turn all too often leads to crap. In other words: what’s the point in knowing all different types of waits available in Selenium if you don’t know how to decide what is a good scenario to automate using Selenium in the first place?

So, instead of delivering my API testing training around REST Assured alone (which I’ve done a number of times in the past), I decided to introduce three different tools to the participants: REST Assured, the open source version of SmartBear SoapUI and Parasoft SOAtest. After an introduction into what constitutes API testing, why it is useful and what you can test using APIs, I let the participants create a number of basic API tests with each of these tools (pretty much the same tests three times over), so they could experience firsthand how the features provided by each of the tools compare. Moreover, since I chose tools that are at opposite ends of the API test tool spectrum (REST Assured is a Java library for RESTful APIs, SOAtest is a commercially licensed enterprise-grade tool that supports a wide variety of protocols and message types, with SoapUI somewhere in between), participants get a much broader view of API testing than they’d get by learning REST Assured alone.

The feedback I received afterwards confirmed what I hoped to achieve with my experiment: all the attendees thought it was great to see more than a single tool, and since I gave them pointers to material for further exploration, they could decide for themselves in which direction their further education will take them.

I recently launched another course in which I try to do something similar, although in another fashion: instead of teaching people how to use Selenium WebDriver (i.e., teaching them the API and some useful Selenium-only tricks), I explain what types of tests should be created using Selenium, and I teach them how I would approach creating readable, maintainable and reliable tests with Selenium, Cucumber/SpecFlow, JUnit/NUnit and ExtentReports. Again: providing context and cutting the crap (you can argue about whether or not I’m covering ‘competition’ in this one) instead of teaching people all of the methods and features of a single tool.

I hope to deliver this type of automation training much more often in the future, and I’d love to see other automation training providers follow suit. For those of you who’d like some more details on the training objectives and subjects covered in this API testing training, please click here.

As always, I’d love to hear your thoughts. What to you constitutes good automation training?