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Apptest.ai Alternative

Testing mobile apps can be challenging due to the complexities involved, such as device fragmentation, OS updates, network conditions, global reach, time constraints, and user behavior. The demand for rapid development cycles often clashes with the necessity for thorough testing.

Traditional testing tools require significant manual effort to write and maintain test scripts, which can slow down the development process. This brings us to an AI-based mobile testing tool called Apptest.ai.

It is a cloud-based mobile app testing platform that leverages AI for autonomous exploration testing. It focuses on simplifying and expediting the mobile app testing process, particularly for those new to automation or without coding expertise.

Features of Apptest.ai

  • Apptest.ai uses AI to generate and execute test cases for mobile applications automatically. The AI engine analyzes the app and creates test scripts without requiring any manual intervention, which can significantly reduce the time and effort needed for test creation.
  • The tool offers a test builder called Stego, which allows drag-drop operations to be user-friendly even for non-technical users. Thus, you can set up and run tests without needing to write code. This makes it accessible to a broader range of team members, not just developers or testers with coding skills.
  • Apptest.ai supports testing across different mobile platforms, including Android and iOS.
  • Tests can be executed in the cloud, which allows for parallel testing on multiple devices and configurations.
  • The tool includes capabilities for visual testing, where the AI can detect UI inconsistencies, layout issues, and other visual defects that might not be caught by traditional test scripts.
  • The tool provides detailed reports and analytics in a graphical way for easier understanding.

Apptest.ai allows you to create test cases by interacting with the mobile app screens.

Every test screen is captured with details.

The AI bot’s exploratory testing paths are captured.

Considerations in Apptest.ai

There are certain aspects that you’ll need to consider when it comes to testing with Apptest.ai.

  • Limited features: Though focusing on AI exploration testing is a strength, it might lack features compared to established, more comprehensive testing platforms. These platforms may offer additional features like script-based automation for more complex testing needs.
  • Learning curve exists: While user-friendly, understanding Apptest.ai’s functionalities and interpreting its reports will still require some learning curve for users new to mobile app testing.
  • Requires additional tools: If you are looking to test websites or desktop applications along with mobile apps, then Apptest.ai isn’t the best option.
  • Nascent community: Since this tool is relatively new in the market, its community is still nascent. Finding enough help can be a challenge.
  • Check CI/CD tool support: While Apptest.ai integrates with a few CI/CD platforms, you might need to see if it supports the ones you use.

Test Automation with testRigor

Tools like Apptest.ai might not work for you for a number of reasons. But that does not mean you cannot benefit from AI-powered testing.

Luckily, there is another competent alternative: testRigor, which works on generative AI.

testRigor is a no-code/low-code test automation tool that uses various forms of AI to make test case creation, execution, and maintenance easier. This cloud-based testing platform offers quick test creation across platforms like the web, mobile, and desktop.

Let’s take a look at what more this tool offers.

Features of testRigor

  • Plain English Tests: With testRigor, you can create test cases in plain English language without worrying about unstable CSS/XPath locators. This is perfect for teams that want to involve non-technical folks in the QA process since there is no prerequisite for knowing about programming languages or implementation details of UI elements. testRigor only expects you to use natural languages to tell what you want it to test. There are a few ways to do this.
    • Write the English test scripts manually or import test cases from test management tools such as TestRail, PractiTest, ALM, etc., to run directly as automated tests.
    • Use the record-and-playback feature to capture the test case when you execute it and generate plain English test cases. You can update and execute these recorded test cases at any point in time.
    • Let the generative AI feature build test cases for you with just a brief description of the test scenario. testRigor will come up with various test scripts that are functional and ready to run. At any point in time, you can edit these tests, which are captured in plain English. You can even create corner cases for particular test scenarios through this generative AI feature.
  • Easy Onboarding and Setup: testRigor does not require extensive training of either your QA team or the tool itself, unlike many other AI-based tools. Just create accounts on this cloud platform and get busy building test cases. If you plan to use the generative AI feature, then you just need to provide comprehensive descriptions to the tool so that it can generate meaningful tests for you. The interface is quite simple, and with documentation available, your team can easily work with it.
  • Single Tool for Many Platforms: Test various applications like native mobile and native desktop apps, web-based apps, ERP and CRM systems like SAP, Salesforce, Oracle, Microsoft Dynamics, and even your legacy systems. Since testRigor emulates a human tester, what goes under the hood of the application under test is of little consequence to this tool. testRigor also offers commands specifically for mobile platforms. This makes it easier to tell testRigor what to do, like “swipe down” or “zoom out “20” % from the middle of the screen”.
  • Supports Various Testing Types: Perform different kinds of testing like regression testing, smoke testing, UI testing, functional testing, end-to-end testing, UAT testing, API testing, and more. It also includes support for visual testing, email testing, file, database, QR code, SMS, and audio testing.
  • Stable Locator Strategy: This tool refers to elements from a human perspective and not from a locator standpoint. This eliminates the dependency on implementation details like XPaths and CSS selectors, which can change frequently. Even if any of these underlying locators change for a UI element, testRigor can still locate it on the UI and carry on with testing, as its focus remains on capturing UI elements as they appear on the UI rather than how they are written in the code.
  • Near-zero Maintenance: You can get ultra-stable test runs and minimal test maintenance as testRigor uses AI here as well to self-heal test cases.
  • Secure Platform: This platform is fully cloud-hosted, which means there are no extra infrastructure expenses. testRigor is also a secure platform that is SOC2 certified.
  • Advanced Reports and Logging: Every test run provides details about the execution, such as screenshots, relevant error messages, which are again in simple English, and video recordings. It also captures technical details, such as console logs and technical errors.
  • Free Account Available: testRigor offers free public accounts that can be created directly via registration on its website. This is a good place to start before advancing to the subscription-based plans.

Here is an example of a testRigor test case. As you can see, these are just plain English test steps. So everyone on your team can create, execute, and update the tests without requiring any programming language proficiency.

You can use reusable rules (subroutines) to group English test steps for use in multiple test cases: ‘set up the app’ is a reusable rule here.

You can view all errors that occurred during the execution of the test suites in one place and act on them accordingly.

Summary

AI-based testing is the new way to go about automation testing. Here’s a quick overview of the two tools.

Parameters Apptest.ai testRigor
AI capabilities AI-driven autonomous testing. Focuses on exploratory testing. Natural language processing (NLP) for test creation. Uses generative AI for maintaining and evolving tests over time.
Primary use case Mobile app testing (Android and iOS). Web, mobile, API, database, and desktop app testing.
Ease of test creation Easy test creation through drag and drop. Plain English descriptions, no scripting required.
Element recognition technique Uses computer vision to recognize patterns and UI elements. Uses advanced AI and computer vision.
Test maintenance Low maintenance due to AI handling updates. Low maintenance due to AI-based handling of UI changes. Upto 99.5% less test maintenance, compared to Selenium.
CI/CD integrations CI/CD integration, particularly with Jenkins. CI/CD integration with Jenkins, GitHub, and more.
Cost SaaS-based pricing and is generally cost-effective. Generally affordable. Pricing can vary and often depends on the scale and features used.
Test customization Limited, focused on autonomous exploration. High, supports custom test scenarios in plain English.
Support and community Growing, but relatively new. Well-supported by support team, active community and documentation.

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