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Top 10 AI-Powered Mobile Testing Tools

Naman Upadhyay
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Naman Upadhyay
  • Feb 22, 2024
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    14 min read
Top 10 AI-Powered Mobile Testing Tools
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We live in a hyper-competitive mobile app landscape and speedy deliveries are mandatory. Did you know that businesses lose an estimated $1.7 trillion annually due to slow updates or malfunctioning mobile apps? User expectations are higher than ever; boost your testing processes with these top-tier AI-powered mobile testing tools.

Key points to keep in mind while selecting a tool.

Selecting the right mobile testing tools is a pivotal decision that significantly impacts testing efficiency. When evaluating these top 10 AI-powered mobile testing tools, consider the following criteria to make an informed decision:

  • Industry Use: Investigate the tool's prevalence and success within your industry. Tools that are widely used in your specific sector may come with industry-specific features and best practices, contributing to more seamless integration into your testing processes.
  • Scalability: Ensure the chosen tool can scale according to your project requirements. Whether you are working on a small application or a large-scale enterprise project, scalability is crucial to efficiently accommodating evolving testing needs and growing test suites.
  • Features: Evaluate the tool's feature set, ensuring it aligns with your testing needs. Look for comprehensive capabilities such as self-healing tests, AI-powered test case generation, and support for natural language processing.

Top-tier list for mobile testing tools

Discover the pinnacle of automation with the Top 10 AI-powered mobile testing tools, redefining testing standards.

1. Applitools

Launched in 2013, Applitools is an innovative visual testing and monitoring platform that stands out for its emphasis on visual AI. This tool provides a unique approach to mobile automation testing by automatically detecting visual bugs and differences across various applications and devices.

USP: Applitools' unique selling point lies in its advanced visual AI technology, which detects and highlights visual differences in applications, making it a game-changer for teams.

Key Features of Applitools:

  • Applitools employs advanced visual AI technology, allowing testers to identify visual bugs and inconsistencies with unmatched precision.
  • Applitools enables seamless cross-browser and cross-device testing, ensuring a consistent user experience across a wide range of environments.
  • Applitools is designed to handle testing at scale, making it suitable for large and complex applications with diverse user interfaces.
  • It seamlessly integrates with popular test automation frameworks, making it adaptable to existing testing workflows.

Target Audience: Development and testing teams seeking precise visual validation for their applications.

Supported Languages: Java, C#, Python, Ruby, and JavaScript
User Rating:
4.4/5 [The rating should be given in stars⭐ instead of numbers.]

Screen Captures: 

Scanning UI

Scanning UI

Applitools UI with 3 different types of execution results

Applitools UI with 3 different types of execution results

Integration with Third-party device provider

Integration with Third-party device provider

2. Functionize

Introduced in 2016, Functionize is an AI-powered testing platform designed to enhance the test creation and execution processes. It stands out by incorporating machine learning and natural language processing to streamline AI mobile testing.

USP: Functionize's advanced AI-powered testing sets it apart by autonomously adapting to changes in the application. This reduces the need for extensive manual intervention.

Key Features of Functionize:

  • Functionize allows testers to write test cases in plain English using NLP. The tool then automatically converts these natural language descriptions into executable test scripts.
  • Functionize incorporates AI-driven self-healing capabilities, automatically identifying and fixing broken test scripts. This significantly reduces the need for manual intervention in script maintenance.
  • The platform provides advanced analytics, offering insights into the performance of applications. Testers can make informed decisions based on comprehensive test results, enhancing the overall testing process.

Target Audience: Teams in search of an AI-driven testing tool that seamlessly adapts to changes, enhancing the efficiency of the testing process.

Supported Languages: No specific language requirement.

User Rating: 4.7/5

Screen Captures

Schedule Board:

Schedule Board

Test Execution:

Test Execution

Results and Recordings:

Results
Recording

3. Eggplant

Eggplant, introduced in 2008, is an AI-driven testing tool known for its holistic approach to test automation. It goes beyond traditional automation by combining test creation, test execution, and performance monitoring into a single platform.

USP: Eggplant's unparalleled strength lies in its intelligent automation, powered by AI. It not only detects issues but intelligently navigates applications, mimicking user interactions for more realistic automation testing tools.

Key Features of Eggplant:

  • Eggplant focuses on user-centric testing, ensuring that applications are tested from the end user's perspective for a more comprehensive evaluation.
  • Using AI, Eggplant generates test scripts by learning and adapting to user interactions, reducing the manual effort required in creating test cases.
  • Eggplant provides real-time performance monitoring, allowing teams to identify and address performance issues during the testing phase.
  • It supports testing across various platforms, including mobile devices, web applications, and desktop applications.

Target Audience: Development and QA teams seeking a holistic, AI-driven approach for testing across diverse platforms.

Supported Languages: No specific language requirement.

User Rating: 4.4/5

Screen Captures:

Integration With SauceLabs

Integration With SauceLabs

4. Kobiton

Kobiton, established in 2016, is a mobile testing platform that specializes in providing real devices for test automation. It offers a cloud-based solution for testing mobile applications on a diverse range of devices.

USP: Kobiton's standout feature is its combined offering of both manual and automated testing on real devices. This ensures comprehensive testing coverage and allows teams to choose the best approach for their testing needs.

Key Features of Kobiton:

  • Kobiton offers access to a vast library of real devices, allowing testers to execute tests on actual mobile devices rather than emulators.
  • It supports parallel testing on multiple devices simultaneously, reducing test execution time and accelerating the release cycle.
  • For organizations with strict security requirements, Kobiton provides the option of on-premise deployment, ensuring data privacy and compliance.
  • Kobiton facilitates scriptless automation, making it accessible to both technical and non-technical users, making it a good choice amongst the various AI-powered mobile testing tools.

Target Audience: Development and testing teams focusing on mobile applications seeking a versatile platform for both manual and automated AI-powered test execution.

Supported Languages: Java, C#, Python, Ruby, and JavaScript

User Rating: 4.3/5

Screen Captures

Configuration

Configuration

Test Results

Test Results

5. Sauce Labs

Sauce Labs, founded in 2008, is a cloud-based testing platform that focuses on ensuring the quality of web and mobile applications. It provides a comprehensive testing infrastructure with a wide range of devices and browsers.

USP: Sauce Labs excels at providing a cloud-based platform for cross-browser and mobile testing. Its real-device cloud ensures testing in real-world scenarios.

Key Features of Sauce Labs:

  • Sauce Labs boasts an extensive selection of devices and browsers, enabling thorough cross-browser and cross-device testing.
  • It allows for parallel test execution in the cloud, significantly reducing test execution time and accelerating the testing process.
  • Sauce Labs provides real-time analytics and insights into test results, helping teams quickly identify and address issues.
  • Seamless integration with popular CI/CD tools ensures that Sauce Labs seamlessly fits into existing DevOps workflows.

Target Audience: Development and QA teams requiring a cloud-based solution for cross-browser and mobile testing to ensure optimal application performance.

Supported Languages: Java, C#, Python, Ruby, and JavaScript

User Rating: 4.3/5

Screen Captures

Analytics

7 Day report

Test Insights

Test Insights

Result Metadata

Result Metadata

6. Bitbar

Bitbar, established in 2012, is a mobile test automation platform that offers a cloud-based solution for testing mobile applications on real devices. It focuses on providing a scalable and flexible testing environment.

USP: Bitbar's strength lies in its extensive real device farm, offering a comprehensive selection of devices for testing. This ensures a minimal risk of post-release issues.

Key Features of Bitbar:

  • Bitbar provides access to a cloud-based infrastructure with a vast array of real devices for testing, eliminating the need for physical device labs.
  • It supports scalable test execution on multiple devices concurrently, enabling efficient parallel testing and faster feedback.
  • Bitbar is compatible with popular open-source testing frameworks, allowing flexibility in test script creation and execution.
  • Bitbar offers performance monitoring features, helping teams identify and address performance issues during the testing process.

Target Audience: Development and testing teams focusing on mobile applications seeking a cloud-based solution with a diverse set of real devices for continuous testing.

Supported Languages: Java, C#, Python, Ruby, and JavaScript

User Rating: 4.1/5

Screen Captures

Live Testing Options

Live Testing options
Live Testing Option_2

Test Execution Overview

Test Execution Overview

7. Perfecto

Perfecto, founded in 2007, is a comprehensive testing platform that covers web and mobile applications. Notably, it includes biometric automation capabilities, providing a unique approach to testing user authentication and security features.

USP: Perfecto's standout feature is its end-to-end testing capabilities across web and mobile platforms. With real device testing and advanced analytics, Perfecto provides a holistic approach to continuous testing.

Key Features of Perfecto:

  • Perfecto stands out by incorporating biometric automation, allowing testers to simulate and verify user authentication using biometric features.
  • It supports end-to-end testing across various platforms, ensuring a thorough evaluation of application functionality and performance.
  • Perfecto facilitates testing on a diverse range of browsers and devices, ensuring consistent user experiences.
  • Perfecto offers scriptless automation options, making it accessible to testers with varying technical expertise.

Target Audience: Development and QA teams seeking a unified solution for continuous testing across diverse web and mobile environments.

Supported Languages: Java, C#, Python, Ruby, and JavaScript

User Rating: 4.4/5

Screen Captures

Auto-Generated Test Steps

Auto Generated Test Steps

8. Testim

Founded in 2012, Testim stands out as a user-friendly test automation platform for web, mobile, and API testing. What makes Testim unique is its community-driven approach, offering a free platform that encourages collaboration among teams.

USP: Testim’s unique selling point is its community-driven approach, offering a free and collaborative platform for test automation. It stands out as an ideal choice for teams.

Key Features of Testim:

  • Testim offers a free test automation platform with robust features, making it cost-effective for small to large teams.
  • It has a thriving community that contributes to the development of add-ons, providing a rich ecosystem of pre-built actions for test automation.
  • Testim supports codeless automation, allowing testers to create and execute test scripts without the need for coding expertise.
  • Seamless integration with popular CI/CD tools ensures Testim fits seamlessly into existing DevOps pipelines.

Target Audience: Development and testing teams looking for a free and collaborative test automation platform that supports web, mobile, and desktop applications.

Supported Languages: Java, C#, and Python

User Rating: 4.7/5

Screen Captures: 

New user browser UI

New User Browser UI

Recorded steps

Recorded steps

Integration options

Integration options

9. Katalon Studio

Katalon Studio, launched in 2015, is an integrated AI mobile automation tool that caters to both beginners and experts. It provides a comprehensive set of tools for web, API, mobile, and desktop application testing.

USP: Katalon Studio's unique selling point is its all-encompassing approach to test automation. It combines an intuitive user interface with rich features, offering a versatile solution for teams with varied levels of expertise.

Key Features of Katalon Studio:

  • Katalon Studio offers an all-in-one testing solution, covering web, API, mobile, and desktop application testing within a single platform.
  • It includes a built-in test recorder, enabling testers to create test scripts easily without manual coding.
  • For users with coding expertise, Katalon Studio supports advanced scripting using languages such as Java, Groovy, and JavaScript.
  • It seamlessly integrates with popular external tools, making it adaptable to different testing environments and workflows.

Target Audience: Development and testing teams seeking an all-in-one solution for web, mobile, and API testing with a user-friendly interface.

Supported Languages: Java, Groovy, and JavaScript

User Rating: 4.4/5

Screen Captures: 

New user UI

New user UI

Recorded test steps

Recorded test steps

10. App Center Test

Previously known as Xamarin Test Cloud, now part of Microsoft's App Center, is an AI-driven mobile testing tool that allows you to test your app on a large number of real devices. It supports Android and iOS platforms and is known for its cloud-based testing capabilities.

USP: App Center Test uniquely combines extensive real-device coverage, parallel execution, and AI-driven scripting to deliver efficient accuracy for a wide range of mobile devices.

Key Features of App Center Test:

  • Run tests concurrently across multiple devices parallelly, significantly reducing test execution time.
  • Leverage AI-powered capabilities for test script generation, enhancing script creation and maintenance efficiency.
  • Test your mobile app on an extensive range of real devices, ensuring thorough compatibility.
  • Access comprehensive test reports with detailed logs and screenshots for effective debugging and analysis.

Target Audience: Development and QA teams seeking an AI-driven mobile automation solution familiar with Microsoft services.

Supported Languages: C#

User Rating: 4.3/5

Screen Captures: 

First-time user UI

First-time user UI

Test Analytics

Test Analytics

Let’s compare these mobile testing tools!

Tool Company Supported Platforms Supported Features Self-Healing Tests AI-Powered Test Case Generation NLP Support Free Trial Ease of Use
Applitools Thoma Bravo Web, Mobile Visual Testing, screenshots, Video Recording Yes No No Yes Easy
App Test Center Microsoft Mobile Automated Testing, screenshots, and recordings Yes Yes Yes Yes Easy
Functionize Functionize Web, Mobile AI-Powered Testing Yes Yes No Yes Easy
Eggplant Keysight Technologies Web, Mobile, Desktop Intelligent Automation, Screenshots Yes Yes Yes Yes Medium
Kobiton Kobiton Mobile Manual and Automated No No No Yes Easy
Sauce Labs Sauce Labs Web, Mobile, Desktop Cross-Browser Testing Yes Yes No Yes Easy
Bitbar SmartBear Software Mobile Continuous Testing, Screenshots Yes No No Yes Easy
Perfecto Perforce Software Web, Mobile Continuous Testing, Screenshots Yes Yes Yes Yes Medium
Testim Tricentis Web, Mobile, Desktop End-to-End Testing, Screenshots, and video recording Yes Yes No Yes Easy
Katalon Studio Katalon Web, Mobile, Desktop Test Automation, Screenshots Yes Yes No Yes Easy

Conclusion

In essence, the rise of AI in mobile testing, exemplified by tools like Applitools, Katalon, and Eggplant, marks a transformative leap in efficiency. Prioritize features, assess industry adoption, and ensure scalability when selecting your tool. The right choice not only expedites testing but is fundamental to the success of mobile development.

Read the next chapter

Frequently Asked Questions

How do AI-powered tools differ from traditional automation tools?
FAQ Arrow

Traditional automation tools rely on predefined scripts and test cases, while AI-powered tools use machine learning algorithms to adapt and improve over time, offering more efficient and effective test coverage with advantages like self-healing ability.

What kind of AI technologies are commonly used in these tools?
FAQ Arrow

AI-powered mobile automation tools often incorporate a variety of sophisticated technologies, including:

  • Machine Learning (ML): These algorithms can predict outcomes based on historical data, which is crucial for identifying potential issues and optimizing test strategies.
  • Natural Language Processing (NLP): NLP allows the tools to understand and process human language, enabling them to generate and execute test cases from plain language descriptions.
  • Computer vision: This technology helps in recognizing and validating UI elements on the screen, even if they change position or appearance, ensuring that the automation is resilient to changes in the app’s design.
  • Emotion recognition: Some advanced tools use this to understand user reactions to the app, which can be particularly useful in UI/UX testing.
  • Chatbots: These are used for automated customer service interactions, which can also be tested using AI-driven tools to ensure they respond appropriately to user queries.
How do AI-powered tools handle changes in the mobile application?
FAQ Arrow

AI-powered tools adapt to mobile app changes through continuous learning, dynamically updating test cases to reflect new features and functionalities. They detect anomalies, suggest changes or issues, and integrate with version control to track and adjust to app modifications. By analyzing user interactions, these tools predict the impact of changes on the user experience, ensuring testing remains focused and effective.

Are there any challenges associated with AI-powered mobile testing tools?
FAQ Arrow

Yes, implementing AI in mobile automation comes with several challenges:

  • Data quality: The success of AI-powered testing heavily relies on the quality and diversity of the data used for training the models. Poor data can lead to inaccurate results and predictions.
  • Model interpretability: Understanding how AI models make decisions is crucial, especially when unexpected outcomes occur.
  • Complexity: Setting up AI-powered tools can be complex and typically requires specialized knowledge in AI and machine learning.
  • Bias and Ethics: AI models can inadvertently learn and perpetuate biases present in the training data, which can lead to ethical concerns, especially in decision-making scenarios.

About the author

Naman Upadhyay

Naman Upadhyay

Naman Upadhyay, a proficient QA Engineer at Alphabin, excels in Python and React, proficiently managing diverse projects. Known for his precision-driven approach, he delivers high-quality software solutions.

More about the author
Join 1,241 readers who are obsessed with testing.
Consult the author or an expert on this topic.
Join 1,241 readers who are obsessed with testing.
Consult the author or an expert on this topic.
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