Manual vs Automated Testing: What Scales Better?

What Scale is Larger for Modern Software? Manual vs. Automated Testing

Why This Manual vs. Automated Testing Argument Still Holds

Every software team performs testing in some capacity; however, not every team will implement that testing method as the software grows.

Quality assurance becomes increasingly challenging to maintain as the number of releases increases, as does the frequency and complexity of the architecture, as products continue to grow.

For newer software teams, they will usually be primarily reliant on manual testing as it is low-cost, easy to use, and allows for more creativity, faster to set-up & execute; however, as the size of the regression suite increases, and as the frequency of release increases, it is extremely challenging for newer software teams to keep up with both of these increasing numbers.

On the other hand, automated testing has the potential for greater speed, more consistency and larger scalability, but it comes with new challenges such as higher initial investment in the tools, increased maintenance overhead, and a more complicated tool selection.

So, “The big question is not which is the ‘best’, but which works the best as the software is scaled, and when does it apply.

This guide evaluates both manual and automated tests in relation to scalability, cost, reliability, tool selection and real-world applications of both types of tests to give engineering leaders the information needed to make the best possible decision.

Advantages of Manual Testing

Manual testing is an especially effective way to test for:

• Exploratory testing
• Usability/accessibility testing
• Early product validation
• Quick feedback on new features
• One-off or infrequent testing scenarios.

Humans can still find visual discrepancies in tests and can see unclear usability flows and edge cases that some automated scripts will miss.

Limitations of Manual Testing

Although manual testing is effective, as the complexity of software grows, the scalability of manual testing starts to falter.

Challenges of scaling manual testing are most evident in:

• The increase of regression test cycles with every software release.
• Inherent human error and, ultimately, inconsistent execution of the same test.
• The length of time between iterations of CI/CD cycles.
• Automated testing often allows you to automate tests for cross-browser and cross-device scenarios, whereas manual testing does not.
• A higher cumulative cost of a number of repetitive labour costs over an extended period of time.

Once your team has started releasing software at least daily or weekly, it will become very difficult to run your entire regression suite manually. Thus, teams begin to use automation.

What Do We Mean By Automated Testing?

Automated testing, also by its own definition, means that you can use automation (scripts and frameworks) to automatically perform tests against your builds, environments, and configurations.

Some automated testing tools that are popular today would include:

• Selenium – Automation of browsers.
• Playwright and Cypress – Modern testing of web applications.
• Appium – Automation testing on mobile devices.
• Testing your APIs is done using Testing Frameworks for inspecting your contracts and integrations.

Typically, automated test scripts are incorporated into the CI/CD pipeline to allow for quick feedback to be generated (see tracks within the CI/CD pipeline image below).

How to Scale Automated Testing

From a scalability standpoint, there are some clear advantages of using automated testing:

1. Speed and Repeatability

Automated tests can run:

• For every code change (Commit).
• Across multiple browsers and devices.

2. Consistency in Executing the Same Steps across Releases.

Automated tests are consistent in executing the same test steps every time. In contrast to manual testing.

For Regression Testing and Large Codebases, a Consistent Approach is Needed

The use of automated testing is highly scalable when deployed with modern architectures such as:

• Microservices Architectures
• API-Based Systems
• Cloud-Native Applications
• Containerised and Serverless Environments

Manual testing cannot keep up with these types of systems.

Cost Considerations: Manual vs. Automated Testing

Many people think that automated testing will always be less expensive.

However, the truth is that the cost difference is not necessarily so cut-and-dry.

Manual Testing Cost

• Lower Upfront Cost than Automated Testing
• But Higher Long-Term Labour Costs for Manual Testing
• Cost is Scalable at a Linear Rate with the volume of Testing
  
  Automated Testing Cost
• Higher Initial Investment for Automated Testing
• Higher Cost of the Tools and Infrastructure to Implement Automated Testing
• On-going Maintenance for Automated Testing Scripts

However, as more tests are executed and more test coverage is developed, the cost of automated testing decreases over time. Automated Testing will become significantly more efficient for Regressions, API Testing, and Performance Testing.

Areas where manual testing is still more scalable

There are still many areas where manual testing remains critical, even though automation has tremendous advantages.

These include:

• Testing New Features and Products (Especially During the Development Phase)
• Continuously Updating UI or Changing Requirements (Rapidly)
• Conducting Exploratory Testing and Ad-hoc Testing (Occasional Testing)
• Ensuring that Accessibility and Usability Testing have been performed correctly

Automated Testing Scripts are successful only when based on accurate assumptions about the functionality and expected behaviour of the system being tested. Humans provide the Contextual Judgments from a User Experience perspective that cannot be accurately included in automated tools.

Challenges Associated with Automating Testing that Organisations Typically Fail to Consider

Automated Testing is not a solution; therefore, it is not always cost-effective. Organisations frequently overlook the challenge of

• Poorly Designed Testing Frameworks
• Ongoing Maintenance Costs for Automated Testing due to Changes in UI
• Flaky Tests (Test Failures), resulting in a lack of confidence in Testing Scripts
• Excessive Tool Sprawl and Additional Complexity Related to Integrating Tools

As a result, many organisations do not derive the expected benefits and return on investment for automated testing. Coding automated testing without a corresponding strategy will result in increased technical debt.

The Role of Manual and Automated Testing in Continuous Integration and Deployment (CI/CD)

The future of software delivery is based on continuous integration (CI) and continuous deployment (CD). To optimise delivery speed and quality, this requires that software be tested as it is developed, allowing businesses to identify and fix bugs before they go into production.

The Role of Manual Testing within CI/CD Pipelines

While many CI/CD teams still use manual testing, it slows down the CI/CD pipeline by requiring the availability of humans to conduct tests. Furthermore, it does not scale with the frequency of deployments.

The Role of Automated Testing within CI/CD Pipelines

Automated testing allows teams to receive continuous feedback on their applications as they are developed (much like CI). In addition, it enables testing to be done earlier in the development cycle (shift-left testing). Finally, because of automated testing, teams practising DevOps or continuous delivery must automate their testing – automation is not an option, it is a requirement for teams practising either discipline.

The Ideal Testing Model: Hybrid

Although there are two methods (manual or automated) for testing, the most efficient testing method is hybrid. High-performing teams will typically use both types of testing. For example, high-performing teams may conduct usability and exploratory testing manually, while at the same time conducting regression tests, API testing and load/performance testing using automated testing.

Evaluating Automated Testing Platforms

When considering an automated testing platform, the following scalability factors will be involved: parallel execution support, cloud-hosted infrastructure, test data management and integration with a team’s existing version control and CI tools. In addition, many teams consider SaaS automated testing platforms, subscription-based automated testing services and AI-based automated testing tools in their evaluation of automated testing tools. Ultimately, teams’ goals are to create automatic and maintainable automated tests.

Can Artificial Intelligence (AI) Improve the Scalability of Automated Testing?

AI-powered automated testing tools are becoming increasingly popular. These tools help teams in the following areas: maintaining test scripts, intelligently prioritising tests, analysing defect patterns and reducing flaky tests. While AI does not replace automation testers, it increases the ratio of signal to noise and enables teams to achieve automation scalability more efficiently.

Manual Testing: The Bottleneck

When Testing By Hand

Manually testing becomes an obstacle when:

• Regression cycles take longer than the sprint length
• Bugs continuously make it through production undetected
• QA feedback is late getting to development teams
• Teams rely on superhero testers prior to deploying

These all point to the need for automated testing to assist with scaling.

The Right Time to Automate

Automation can also be misused, as it is usually not required when:

• The product still needs to prove its “core” assumptions
• Features are changing regularly
• The test scenarios are only valid for a short time frame.

For these reasons, manual testing will still be more effective at scaling until there is sufficient volume in place to support it.

Manual vs Automated Test Solutions by Size Team

Startups

In the beginning, the majority of all testing is done using a manual approach while automating as teams establish initial processes.

Scale-Ups

Automated testing is needed early and often for Regression Testing and API Testing.

Enterprises

Automation is part of the foundation, but it must still include targeted manual testing efforts.

Final Summary: What Scales Better?

If we define scalability as being able to grow without negatively impacting Delivery, then Automated Testing clearly scales better.

However, Scalability is not simply about Speed.
It is also about Sustainability.

Manual Testing offers Flexibility & Insight; Automated Tests provide Consistency & Speed. Teams willing to utilise both Methods in an Integrated Way will likely be the Teams that scale the Best.

At Logiciel Solutions, we assist teams in designing Scalable QA Solutions through a Balanced Approach between Manual Testing Expertise & Automated Testing by AI-first frameworks. The Outcome is Rapid Delivery, Lower Risk, & Quality that will Scale Redundant with Product Growth.

If you feel like your Testing Model/Approach is hindering you, the issue is not typically solely Manual or Automated. It’s about how they can best be integrated.

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