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8/25/2022
10 minutes

Top Benefits of Low-Code Testing For Your Enterprise

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Team Copado
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Low-code testing is an often overlooked part of the development process. In all the excitement of adopting a new way of working, it's easy to overlook the fundamentals. But even though low-code offers an easier interface, it is still coding — and it's still a risk. Every low-code platform has a common vulnerability; you are responsible for anything you create. Build something that's flawed and the subsequent breach or broken software is your problem.

Testing helps enterprises overcome that vulnerability, but often testing solutions are just as cumbersome as coding from scratch. Pairing a low-code platform with a low-code testing solution allows you to realize all the benefits of the changing development environment while minimizing the risk. 

What is Low-Code Testing? 

It's important to clarify the difference between low-code and no-code platforms because they pose different risk levels. In no-code, a user can't change the underlying codebase. They're limited to drag and drop, point and click features. In low-code, users can access and customize the codebase to some extent. Salesforce is a prime example of a low-code platform. Many of its features are point and click-driven, but there are opportunities to customize underlying code.

Low-code provides more flexibility, making it a preferred option. But with custom code and configurations comes risk. Users with the ability to access code also have the ability to break it.

Low-code testing solutions use simplified interfaces to allow the low-code user to create their own tests for those customizations. Of course, low-code testing can be a very broad term. For the purpose of this piece, we're discussing testing tools that are: 

 

System-Agnostic

Declarative

AI-Enabled

Systems don't work in a vacuum. They are small parts of complex ecosystems. Low-code testing tools must be system agnostic to support end-to-end testing. The ability to test for a variety of devices at the same time is also a time saver. 

Low-code users are used to telling systems what they want to happen, not how to get it done. Tools that allow users to record themselves going through the process to create test cases are good examples of declarative philosophies in action. The user gives the system the goal, so it knows if the code is taking the appropriate path. 

Automated tests may require maintenance to stay up to date with system changes. AI-enabled tools will track these updates and change tests to fit new parameters in response. These self-healing capabilities cut maintenance in half. 

 

Low-code testing tools with the above features make it easier to customize solutions and ensure they're correct. Enterprises that use them can enjoy a range of benefits from cost-cutting to employee engagement. 

5 Benefits of Low-Code Tools for Testing 

The right low-code tools for testing don't just improve development. They have indirect benefits that enhance organizations from the bottom up. Here are just a few low-code testing tool benefits. 

#1: Speed

Low-code allows enterprises to hit the ground running because the tool is already in place to support the project. Think of it like asking an employee to create an Excel spreadsheet of last month's sales figures versus asking an employee to design an entire database for storing sales numbers and then adding that information. With low-code, a big part of the work is already done. In testing, that can cut the time commitment from days or weeks to hours. The developer can create their own test and users can record processes directly rather than seeking outside help. 

#2: Upskilling

Low-code has allowed enterprises to upskill many of their business process experts into technology leaders, but there is a gap. That gap lies in testing. This is an overlooked low-code development area that poses a risk for enterprises. Offering a tool that simplifies testing doesn't just get the task done — it teaches the workers about the mechanics of code testing itself. A new focus on testing upskills the worker as they complete a necessary task for system viability. 

#3: Cost

It is less costly to upskill someone to work in a low-code environment than it is to hire a full-time developer. However, that comes with a caveat. There are tasks that only developers with traditional experience can handle. The more of those a business requires on staff, the higher their costs go.

Some enterprises may want to contract out testing work to create their tests, but that doesn't account for maintenance. Just because the code works now does not mean it will work after the next round of updates. Keeping developers on staff just to address those issues is expensive.

Low-code tools can allow individuals to manage their own maintenance and testing updates. When solutions have self-healing capabilities, many tests will course correct in the face of updates, significantly reducing maintenance costs. 

#4: Bottlenecks

Because customized code must be checked by an expert, it's delayed as it sits in a queue awaiting review. That creates bottlenecks that build on each other. By building testing into the development process through low-code tools, enterprises eliminate that step. When testing is continuous and truly integrated into your delivery pipeline via low-code tools, you can overcome the testing bottleneck and innovate with speed and quality. 

#5: Employee engagement

Enterprises really underestimate the effect that technology has on the employee experience. In fact, employees now cite it as a key factor in their workplace engagement. With a shift into hybrid work policies and blurred lines between business and development, it's even more critical now that tools be well built, easy to use, and intuitive. That experience allows them to complete tasks without frustration, setting the tone for a positive experience and long-term success.

As low-code development grows in popularity, so will the need for low-code testing. Enterprises can save money and upskill their workforce by using tools to address the gap. The best ones will use AI and declarative programming languages to manage the entire end-to-end testing ecosystem.

 

 

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