In the car world, manual transmissions are all but a thing of the past. However, many car fanatics still drool over exotic cars with gated manual shifters. This is not the case in the world of continuous testing. Where automated transmissions are seen as taking the joy and activity out of driving, automated testing is becoming an increasingly important part of the SDLC.

Software is being developed faster than ever, and when you need to ensure that your releases are on time, at scale, and highly functional, manual testing is seen as inefficient and oftentimes impractical. The rise of automation testing tools can be attributed to these challenges. The idea is to have solutions and tools that give dev and testing teams a faster, more reliable, and cost-effective way to test software applications.

The key advantages of automation testing tools include the following:

  1. Faster Testing: Automated testing runs continuously and quickly reducing testing times.
  2. Reliable Testing: Ensuring tests are consistent and repeatable eliminates human error
  3. Increased Coverage: Executing tests that cover a wide range of scenarios improves test coverage and ensures all scenarios are tested
  4. Reduces cost: Automated testing tools reduce the need for manual testing, and allow testers to work on more complex scenarios
  5. Scalable: Large applications can be tested easily with automation testing tools, which makes it easier to execute tests on a large scale

Manual vs Automation: The Good and the Bad

  STRENGTHS WEAKNESSES
Manual Testing
  • Human interaction: People testing manually have the experience and intuition to test the scenarios that automated tests might miss
  • Exploratory testing: Manual testers can explore the web or mobile app under test and find unidentified or unplanned issues
  • Cost-effective: This can be a less costly option when dealing with a smaller project or if an investment in automated testing is not possible
  • Flexible: Manual testing can adapt more quickly to project requirement changes
  • Time-consuming: Large and complex testing projects can take a lot of time
  • Poor coverage: Manual testing only covers a limited scope of scenarios as a result of time constraints
  • Error-prone: Manual testing is subject to human error and false results
  • Repetitive: Manual testing can lead to boredom and fatigue for testers
Automated Testing
  • Saves time: Automated testing runs faster than manual testing
  • Scalable: It is simple and effective to scale up testing to cover more scenarios
  • Consistent: Can run the same tests over and over without human error
  • Comprehensive: Covers a large set of scenarios and detects issues that were missed in manual testing
  •  
  • High cost: Automated testing requires investing in software, hardware, and training
  • Limited scope: Testing is limited to predefined scenarios, automated testing tools cannot interact with an application like a human
  • Maintenance: Tests require upkeep and maintenance especially when there are changes to the application a time-consuming process
  • False positives: Producing a false positive when automation testing could require more manual testing

Do You Even Need an Automated Testing Tool?

Automated testing tools are extremely useful in continuous web and mobile app testing. Even though many, if not all, organizations are engaged in some form of digital transformation, it takes some convincing to prove that such a tool is needed at all.

Dev, QA, and testing teams that find themselves constantly performing repeated tasks might want to look into automating those tasks. Additionally, teams with complex scenarios that require multiple steps to complete are vastly aided by automation that ensures tests are performed consistently and accurately. Another use case that helps drive the need for test automation tools is regression testing. When running sets of tests on an updated codebase to make sure that the new update did not introduce a new bug, automation is a huge benefit.

Testing and dev teams that have a CICD pipeline definitely need automation as an essential piece of the pipeline. They can integrate tests into the pipeline ensuring that code changes are not breaking the functionality.

By taking a deep dive into your testing practices and looking at how long your sprints take, how long testing suites take, and how long it takes for a new version to be released you will quickly discover that you do indeed require an automated testing tool.

The Digital.ai Difference

Digital.ai Continuous Testing offers comprehensive support for automation testing tools. The solution as part of Digital.ai’s broader AI-Powered DevOps platform provides features that enable users to execute and manage automated testing. It also provides reports and analyses on test results, making it even more beneficial.

For users of other automation testing tools, Digital.ai continuous testing integrates with Selenium, Appium, and HP UFT. With these integrations, users can create, manage, and execute their automated tests from within their own platform so they can use the tools they are already familiar with to start testing faster.

Supporting the automation testing process is the most important capability and the features that make up the solution are designed for this goal. Test creation and management tools include support for different testing frameworks and languages. Support for parallel test execution across environments and on a huge matrix of browsers and devices will help speed up the testing. The Continuous Testing Reporter, provides insights into individual tests, while the Continuous Testing lens gives users a deeper dive into metrics and analytics that can help track the overall testing process and identify issues before release.

Standing Out From the Continuous Testing Crowd

The uniqueness of the offering is what sets Digital.ai Continuous Testing apart from other automation testing tools.

Firstly, the solution is an open one that integrates with other automation tools. The benefit is that existing tools and workflows from other platforms can be leveraged and integrated into Continuous Testing without drastically changing existing processes. With the included end-to-end testing capabilities users can manage their entire testing process from within this one tool without needing to switch contexts.

Analytics is another differentiator in that Digital.ai Intelligence provides users with dashboards and analytics meant to help monitor and analyze test results in real time. Support for parallel execution and a matrix of real mobile devices and browsers to test against helps increase speed and scale by running tests across different environments.

Another set of integrations that help the tools stand out are integrations with DevOps and CI/CD tools. It provides users with the ability to integrate testing into the DevOps workflow which will improve the SDLC overall.

Some organizations are not sure if they need an automated testing tool. Others might think they have the perfect one right in their back pocket. The truth is that having an open solution that provides end-to-end testing combined with great integrations, advanced analytics, and scalability will help improve your web and mobile apps and even help them rise above their competitors. Anyone looking to streamline their testing process, improve their software quality and accelerate development and delivery should take a long look at Digital.ai Continuous Testing for help meeting those needs.

Related Resources:

Automation Testing Tool Starter Pack
These Key Factors will Help you Choose an Automation Tool
Continuous Testing
Automated Testing

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