How Automated AI Testing Tools Are Redefining The Testing Process

Software testing is an incredibly time-consuming and costly process. 47% of testers state that manual testing can take between 3-5 days and can be 15-25% of your entire project cost.

Thankfully, automated tools have drastically decreased this timescale to about 3-6 hours. This has meant that 97% of software testers are now utilizing automated test suites rather than human intervention.

A graph that shows that 97% of software testers use test automation.

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However, automation engineers are now looking towards artificial intelligence and machine learning algorithms to optimize the testing process. In fact, 57% of QA teams are now using AI to author, execute, and maintain end-to-end testing effectively and efficiently.

So, come with us as we examine how this exciting new testing process can transform your project workflow from a massive waste of time to a lean and effective technology.

What are test automation tools?

Before we look at the best AI testing tools, let us briefly discuss what automated testing is for those not in the know.

Before launching a new software, mobile app, or web application, companies want to make sure their product functions correctly. This is where automated testing comes in. 

An infographic that shows the many benefits of automation testing including, fast, reliable, reusable, improves accuracy, saves time and money, reduces and humans error.

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Manual testing methods involve labor-intensive effort to examine the quality assurance of a product. However, an automated framework eliminates the need for human intervention by using complex algorithms and test scripts to perform continuous testing (also known as agile testing). 

The many different types of automated tests are often split into two distinct categories:

  1.  Functional testing: These tools check the critical features of the software that affect functionality are working
  2.  Nonfunctional testing: These tools test the features that are not crucial to the functioning of software 
An infographic that shows the types of functional testing that includes, unit testing, integration testing,, system testing, and acceptance testing. It also shows the non-functional testing including, performance testing, security testing, usability testing, and compatibility testing.

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Below is a handy table that details what each type of test case entails.

Types of TestingDefinition 
Acceptance testsLooks at how acceptable the end product is for users
Integration testingTests that different components of the software can interact with one another
Unit testingChecks out specific sections of code
Smoke testingExamines if an application works after a new build without ‘catching fire’
Regression testing Makes sure that new code does not interfere with old code. 
Performance testingCompares the software’s performance to Key Performance Indicators (KPIs)
Security testing Analyzes the systems for threats, risks, and vulnerabilities
UI testing Replicates the typical user experience 
API testingVerifies the application program interface is functional

The many benefits of AI testing 

Traditional test automation platforms like Selenium and Appium can work wonders for businesses. However, the introduction of artificial intelligence and machine learning has revolutionized the software development industry. By leveraging these two incredible technologies to run tests, companies can experience countless benefits. 

An infographic that shows the advantages of AI in software testing including, enhanced accuracy, greater test coverage, savings in time and money.

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  1. Codeless testing: Through the combination of artificial intelligence and Natural Language Processing (NLP), test creation is accessible to everyone. It allows testers to write prompts in plain English, which a sophisticated AI then translates into code.
  2. Time-saving: Manual testers have the repetitive task of trawling through thousands of lines of code to identify errors. This is undeniably time-consuming. AI can instead examine code 15 times faster, taking seconds rather than hours.
  3. Scope: The average test coverage, the percentage of code tested by manual and automated tests, is about 30%. However, AI covers an incredible 90% of code in under a year.  
  4. Pricing: In terms of cost, AI testing is significantly cheaper than hiring an entire team of testers. A full team would include the following members of staff: 
A table that shows the average salary of a software testing team which range from $24-$45 per hour.
  1. Accuracy: Test scenarios become significantly more accurate with the application of AI tools. Manual testing is prone to human error due to the tedious nature of the task. In fact, 59% of businesses claim that human error is the main reason for unexpected software downtime.
  2. Test maintenance: AI testing is self-healing, meaning that it is adaptive and can react to changes in the code, unlike traditional automation frameworks. This means there is no need for continuous system maintenance, which reduces costs and saves time. 
  3. True continuous testing: Artificial intelligence enables testing to be done continuously on software, instantaneously identifying errors and issues. 

Our 2 favorite AI testing tools

While there are many artificial intelligence automation testing tools available, the following two choices are absolutely perfect for DevOps engineers, QA teams, and digital transformation teams. 

1. Applitools 

Believe it or not, a well-constructed user interface (UI) can raise your conversion rate by 200%, and an optimized user experience (UX) can boost it by an astronomical 400%.

The homepage of Applitools that proudly declares its goal to 'create visually perfect digital experiences'.

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Applitools is fully aware of the importance of successful UX and UI. Therefore, it has created AI-powered visual testing software that can detect bugs such as overlapping buttons or incorrect layouts. 

Applitools recommends these team members use visual testing:

  • Developers: Test that front-end components and layouts work correctly.
  • Testers: Increase the speed of manual testing by using visual regression tests that can locate issues that are not even being tested for.
  • Designers: Check that the formatting and design are satisfactory and meet brand guidelines.

Wondering how this fantastic AI tool works? Here is our step-by-step guide for getting started with Applitools:

  1. Insert: Simply import Applitools into your test scripts that analyze test screens and end-to-end scenarios. These can be either created by open-source frameworks or proprietary tools.
  2. Train: Teach the visual AI the required parameters by annotating elements, setting match level strictness, and omitting regions of the app.  
  3. Run: Allow the software to run within your infrastructure against local browsers (Chrome, Firefox, Edge, Safari), devices, and cloud-based labs. However, for the best results, use Applitools’ own Ultrafast Test Grid.
  4. Analyze: Examine the test results with the countless features of the AI tool, including root cause analysis and auto-maintenance.
An infographic that shows how a visual testing platform works in four steps that are: test, train, run, and analyze.

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The benefits of using Applitools are endless, but here are some of the highlights:

  • Automated locator tracking: DOM (Document Object Model) is an HTML document accessible by Javascript. Locators allow users to select specific DOM elements to manipulate. Applitools claims that this method is ‘flaky’ and offers visual navigation as a better alternative.
  • Root cause analysis: This feature allows you to find the specific change in coding that caused a test failure, meaning fixes are a breeze. 
  • Localization: The tool allows you to effortlessly test different languages and locations with minimal fuss.
  • Omissions: Create specific parameters that ignore certain elements of your user interface to dramatically reduce false positives. 
An infographic that shows the benefits of Applitools including, automatic locator tracking, root cause analysis, and localization testing.

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2. Testim.io

Testim Mobile is the ultimate mobile testing tool for IOS and Android. The software’s main goal is to help ‘release mobile apps faster’.

The homepage of Testim that proudly states it goal as being 'release mobile apps faster'.

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To do this, the tool eradicates the challenges associated with traditional mobile testing. These challenges include: 

  • Variation: Mobile devices and operating systems vary significantly, resulting in app failure.
  • Coding: Mobile testing often involves the need for coding skills, making the process inaccessible to most.
  • Stability: Changes in the code will result in a test failure.
  • Localization: Some apps rely on GPS data, meaning that tests must simulate different locations.
  • Hybrid: Mobile apps can integrate with web applications.

To tackle these challenges Testim has utilized AI to redefine mobile testing by using:

  1.  Fast, flexible authoring: Low-code testing is fast and accessible meaning anyone can quickly create tests. 
  2. Flexible test steps: Testim allows you to insert code into any step so that the test can overcome any unique challenges your app presents.
  3. Stability backup: The software uses multi-attribute locators meaning that if any locators change, Testim can still locate the element using alternative attributes. 
  4. Fast device management: The ability to easily connect to Android and IOS devices remotely or locally makes testing simple and efficient.
  5. Application management: Conveniently access your latest app files from an online repository for testing. 
  6. Troubleshooting: Locate and resolve errors with ease as the software performs root cause analysis. This will show both network and console logs while suggesting potential causes of the error.
A screenshot that shows how easy it is to run tests with low level coding.

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This fantastic tool can be used to optimize the workflow of three key types of users: 

  1. Engineers: Spend more time creating an innovative app by minimmizing the time performing and maintaining tests. 
  2. Agile Teams: Accelerate the launch of apps by providing the tools necessary for your team to streamline the testing process. 
  3. Salesforce Admins: Use Testim to test Salesforce applications to improve productivity and customer interactions.
An infographic that shows that teams should test Salesforce to improve customer interaction and productivity.

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Applitools and Testim.io integrations and plugins

Both of these tools feature a fantastic selection of plugins. Check out the table below for a full list of available integrations.

ToolIntegrations and plugins
ApplitoolsGitHub, Selenium, Cypress, WebDriverIO, Storybook, Teams, Slack, TestCafe, Watir, Protractor, Playwright, Espresso, Appium, Robot Framework, GitLab, BitBucket, Jenkins, Travis, Circle CI, Semaphore, TeamCity, Bamboo, Azur DevOps, AppVeyer, Jira, Rally
Testim.ioAzure DevOps, Bamboo, Circle CI, Codeship, Jenkins, TeamCity, Visual Studio, GitLab, GitHub, SeaLights, BitBucket

Time to embrace AI automation

Whatever you are testing, AI testing tools are the answer to streamlined and optimized software development.

While we have focused on our top two picks of AI software, these may not necessarily meet your needs and requirements for testing. So, here is our list of honorable mentions::

  1. Virtuoso 
  2. Leapwork
  3. Tricentis
  4. Functionize
  5. Mabl

Still looking for the perfect AI test automation tools? Take your time and shop around to find the ideal test automation tool for your needs.

Take charge of your testing now and head to Top Apps to explore our extensive library of apps guaranteed to revolutionize your software development.