Low-code – the Bigger Picture

Low-code test automation is part of a bigger trend in IT. Forresters and Gartner call it the “Citizen Developer” – the general idea that many business activities can be achieved by business users and citizens directly without the need for big IT projects… initially.

For the last 10 years we have mockingly called Robot Process Automation (RPA) a “poor man’s integration”, in the sense that instead of building sic “real” integration, we build an RPA robot to handle the interface. But it’s equally low-code when your Apple Shortcuts trigger application events or you use Airtables or SmartSheets instead of MS Office tools.

In the mocking from IT teams, we do tend to forget that low-code tools are a short-term efficient and user-friendly way for organizations without a big IT budget to solve some common problems. That it can very well make business sense to RPA data between systems until the last silo has been cemented over.

There is a clear trend that the business units of large enterprises are getting more tech-savvy and can do more IT things on their own: order a new OS, configure a new form, populate tables, and configure collaborative work products. Previously these actions would have mockingly been called “shadow IT” when outside the realm of the IT units. Now it’s more out in the open – and where the IT spend money is.

Low code is, when you squint at it, all about the visualization and abstraction of something that previously took coding in IDEs, tinkering in Excel sheets, and similarly skilled IT labor to configure. It’s really nothing new in the history of IT. For large global enterprise companies, it has always been about consolidating business IT systems and redefining new coherent ways of working.

Replace the existing system suite of 10+ tools with one Software-as-a-Service Solution to create and maintain product information, so that it can be kept in one place and inspire additional digital transformation.

The strategic objective for a large global company in 2022

The current journey for these global enterprises is to move the IT savvy-ness into the business units and make the business units more autonomous in their IT spending. There’s no need to hire an external outsourcing company to maintain the IT operations when most can be done by a few internal staff inside the cloud dashboards or similar admin modules of Salesforce and ServiceNow.

Give it some time, though.

While low-code and RPA can in some cases be effectively coded by business experts – they will soon need some good old computer science techniques to maintain the RPA and low-code shoe strings. At the end of the day, visual code is still code. And low-code test automation is just part of a bigger picture.

Factor in the Ripple Effects

TL;DR: Investing in basic tooling and automation improves your team besides expected metrics.

I work mostly with the implementation of enterprise SaaS systems these days. Large global companies are consolidating custom-built applications and on-premise applications with web-based standard solutions in the cloud aiming for “one standardized source of information to enable digital transformation”.

Yet the testing tooling hasn’t caught up. One company with €5000 million in sales is still using Word documents for test cases and “party like it’s 1999“. They are reluctantly considering tooling to support more agile ways of working. The whole “automate the knowns-knowns” is still pending an evaluation of return on investment (ROI) into technology from 2015. As of writing, Anno Domini 2022.

Assumptions

  • Writing test cases in documents takes about as long as writing automation
  • Maintaining automation is a more explicit task, humans can more easily apply a bit of fuzziness
  • When automation is in place, the execution requires limited efforts to run
  • The alternative to automated test execution is hours of people following and filling out the documents

With the investment in the tool, there’s a break-even around XX hours of document-based testing a month. That is if we plan for more than XX hours of document-based testing a month, the investment pays off. Your Mileage May Vary

But there’s more to it

First of all, when automated test execution is at limited costs to run and it can run independently at night, you will get the same effects as Continuous Integration and nightly builds have had in software development: you tend to run them more and more often.

This enables faster feedback both with regards to confirming new features and sums up to more effective regression testing. I have seen this happen in both custom application development and configuration of web-based standard solutions. In one project where I added automation, we have run nearly 8000 automated runs in a year (and 200 SME-based). We actually run the tests more often, and we cover the important things every day – and everything often enough. We do in fact get more testing, and broader coverage than any document-supported testing could ever scale to do.

Believe the experts

While there is some vendor basis in the following two webinars, the story is the same: Test automation can accelerate IT deliveries:

Alternatively, look into the research from Accelerate – and the DevOps handbooks. The ripple effects of automated test execution are plenty and go beyond the math of the testing effort. One thing to keep in mind is that test automation itself is not enough. At first, you need transformational leadership.

Hunches and Hard Truths

Recently I was in a network call on the use of automation and machine learning in detection of skin issues (EDB 5.0 in Danish only). Similarly I was reading about automation in the legal space. Both these stories align with the struggles we see in the discussions around how much we can automate. We can model it on this simple continuum between hunches and hard truths:

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Conway’s Law for Test Automation?

Any organization that designs a system (defined broadly) will produce a design whose structure is a copy of the organization’s communication structure.

Melvin E. Conway via Wikipedia

Conway’s law continues to be one of the hard truths in IT deliveries. It tells us that solutions are shaped – by the shape of the delivery organization. While Conway’s law is usually seen on a macro level (Just Eat UK is an example) – it also applies to smaller units (see the Angel of North anti-pattern).

As software test automation becomes more and more like a software development project – I would hypothesize that Conway’s law indeed predicts the shape of the (test) automation solution. So in other words, if the shape of your automation is a pyramid/triangle, so is your team structure heavy on development tests.

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Darlings, Pets, Cattle and GUID’s

Kill your darlings and treat your tests more like cattle than pets, are among some of the heuristics currently around for managing your environments and automation test suites. These heuristics tells me that the environments and automation are in a state of product or even commodity, while previously the tests and environments where like darlings and pets – named and nurtured.

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Automation is for Other Roles Too

Automation of business tasks is no longer for the software developers only. Similarly test automation is no longer for testers and test engineers only. Both these trends help to create smarter testing performed by non-testers.

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Align you Test Strategy to your Business Strategy

Obviously! – But often where we fail to do this as testing professionals. We get caught up in terminology discussions, application of standards and obligations and who gets to do the work – that we forget to align with the business side of things. And thus the beatings continue until morale improves – if you don’t align you test strategy to the business*.

The business side can be hard to read. Also coming from the back story that testers long for objectivity – and “just” want to state the facts for the decision makers. I know, I’ve fallen into that trap many times.

We need to be able to read the business strategy and prepare the test strategy accordingly... and business decisions first.

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It’s a Model – not the Truth

Usually when we discuss Observability, Testability, Modern Testing Principles, it should be with the disclaimer from what context the lessons originate and that Your Mileage Will Vary.

There are so many different IT projects out there – that assuming every IT project is about source code is quite a blind spot. Projects that deal with commercial standard systems or outsourced software might have source code underneath – but many teams does not have access to the source. Additionally, many legacy systems from the 90’es and older does not have the same automation capabilities as we have now.

Not all software projects are about consumer facing native apps and websites. While they are numerous there’s still plenty of systems out there for internal and business-to-business use. While the trends from CI/CD are picking up for B2B and internal systems, things doesn’t move so fast.

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Explore, Code and Business

There are plenty of contexts where testing happens that doesn’t formally involve testers, or formally involve a testing phase. Still contexts like those have testing as an implicit activity.

We are neglecting the business know-how when all we talk about wrt. smarter testing is either the practices of exploration or of coding. Let’s bring in smarter testing for the business and coding sides too.

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RPA – Tomorrows Best Practise

Recently I was reviewing the offering of the Microsoft Power automate desktop offering, and I realized: Robot Process Automation is still the rave – every tool vendor and their dog has an offering in this space:

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