While test automation can’t replace manual tests in many cases, automation can ensure your testing strategy delivers the maximum return on investment possible.
Not only does automation shorten dev cycles, but it also helps you avoid repetitive tasks and improve software quality.
However, choosing the right approach is essential to get the most out of your tests. In this article, we’ll explore five different automation approaches that may work for your software.
The 5 Best Automation Testing Approaches
Before switching your automation approach, it’s important to learn how automation testing works and its many uses. From there, you can explore the following industry-standard techniques.
1. Record and Playback
Record and Playback (R&P) is a basic automation approach with limited long-term utility and flexibility. Testers can record user actions and replay them back multiple times to compare actual results with what’s expected. R&P relies on hard-coded data and software tools.
R&P is useful for short, basic projects with a limited duration like exploratory and entry testing. It’s an ideal way to get into test automation due to its low development cost and ease of use since coding knowledge isn’t necessary. However, this technique has limited coverage.
2. Record and Playback (Enhanced)
R&P Enhanced is a similar automation approach to standard R&P except its framework provides more functionality by enabling more use cases and parameterized data.
Once again, R&P Enhance is dependent on tools but requires more programming knowledge to initiate.
It’s possible for programmers to see an immediate return on investment for a single project, especially if testing only includes short-term tests and limited checkpoints. For long-term projects, R&P Enhanced can burn a hole in your pocket from high maintenance costs.
3. Keyword-Driven Frameworks
Keyword-Driven Frameworks is an advanced testing approach that works in two stages: design and development and execution.
While you will need sophisticated coding skills, time, and the right tools to maximize value, key-driven frameworks are ideal for most projects and data sets.
Unfortunately, higher performance comes at the cost of a significant upfront investment to implement its framework. But, teams who use this framework benefit from script useability and reusability, the ability to reproduce test results quickly, and a wider test flow coverage.
4. Data-Driven Frameworks
Data-Driven Frameworks are ideal for advanced testing needs that are repetitive and include large data inputs.
In this framework, programmers will create test scripts that run together within related data sets, meaning the controls and environment settings can’t be hardcoded.
Similar to Keyword-Driven Frameworks, this framework has great usability and reusability, reproducible results, and an optimate test flow coverage.
However, Data-Driven Frameworks require frequent manual intervention and great programmers to undertake their implementation.
5. Data/Keyword-Driven Framework Hybrid
By combining two frameworks, you can satisfy almost all of your organization’s automation requirements across environments and applications.
A hybrid framework offers high support for distributed testing teams and is ideal for changeable, large, and transitioning data sets.
Although hybrid frameworks are flexible and comprehensive, several challenges involve their implementation. Ongoing maintenance is an issue, and only the most experienced programmers can use hybrids, which limits ROI and could be considered “overkill” for small projects.
Which Testing Approach is Right For You?
Record and Playback, whether it’s in its enhanced or standard form, should be used for small teams who take on limited projects.
Data-Driven Frameworks are perfect for mid-sized teams who need a less expensive but complex approach to large-scale, repetitive tests.
Keyword-Driven and hybrid frameworks are only applicable for large teams due to their complexity and overhead costs. All approaches should use automation tools in their framework.
There’s a right and wrong way to initiate automatic tests, so you should consider costs, technical considerations, and complexity, as some approaches may be unsuitable for your projects.