AI and machine learning can help to automate the testing process by generating test cases and test data. They can also help to identify errors and potential areas of improvement. In addition, AI and machine learning can be used to create virtual environments for testing, which can be more realistic and representative of the real world.

As the use of AI and machine learning in testing becomes more widespread, it is likely that the role of human testers will change. They will become more focused on overseeing the automated testing process and interpreting the results.

The future of software testing is likely to be more efficient and effective as a result of the increasing use of AI and machine learning. This will benefit both developers and users by reducing the time and cost of testing, and by improving the quality of software products.

This tool is now one of the most demanding test tools in the parket. UntimateQA is offering a free course on applitools. All folks who are currently working on Selenium should undergo thos course.
Link to course: https://courses.ultimateqa.com/courses/applitools (website seems still under development, but you can enroll the course)

Training Content

Part 1: Getting started

• 00-Course overview
• Course prerequisites
• 03 Course syllabus
• How to download and install Visual Studio
• Create Applitools account and install Nuget packages
• Why must we automate visual testing
• Benefits of Applitools

Part 2: Baselines and Dashboard

• What is a baseline in Applitools
• 01-Code overview
• 02-Baseline examples
• 03 1st comparison
• 04 Zooming, resizing and layers
• 05 Toggling and Floating region

Part 3: Match Levels and Regions

• 01 Exact match level
• 02 Strict match level
• 03 Content match level
• 04 Layout match level
• 05 Introduction to Ignore regions
• 06 Ignore regions in code
• 07 Ignoring multiple regions
• 08 Floating region
• 09 Strict region
• 10 Content region
• 11 Layout region

Part 4: Test Manager

• 01 Test Manager UI
• 02 Batches
• 03 Full page screenshots with CSS stitch
• 04 CSS stitching vs standard scroll
• 04 Bugs and test steps in UI
• 05 Test steps code
• 07 Fluent API
• 08 How programatic regions look
• 09 Conclusions

Tariq King is the senior director and engineering fellow for quality and performance at Ultimate Software. With more than fifteen years’ experience in software testing research and practice, Tariq heads Ultimate Software’s quality program by providing technical and people leadership, strategic direction, staff training, and research and development in software quality and testing practices. His primary research interest is engineering autonomous self-testing systems. He is cofounder with Jason Arbon of the Artificial Intelligence for Software Testing Association.

Here is the Video:

Intelligent Digital Mesh:

Intelligent Digital Mesh is the mesh of people, devices, digital content and services. It will transform the mobile businesses and apps.

1. Intelligent apps use AI and machine learning to interact in a more intelligent way with people and surroundings. A recent example is Google’s Motion Sense feature in pixel 4 (radar-based technology developed by Google) where you can control apps on mobile by moving hand/fingers in air without touching the mobile screen.

Soon this will be adopted by mobile apps and the challenge will be how to test such features. Next is what if we implement AI/ML in Motion Sense tech where system learns the user gestures.

2. Conversational platforms (like Alexa, Google Assistant, Siri) when integrated with digital twins or AR/VR and mixed reality are changing the way that people perceive and interact with the digital world and devices.

3. Block chain, event driven when combined with AI/ML and Conversational platforms will make the testing further complicated.

We need to build strong AI/ML automated algo for mobile testing to test all the above mentioned stack.

Gartner – Top 10 Strategic Technology Trends for 2017
Gartner Top 10 Strategic Technology Trends for 2018
Gartner Top 10 Strategic Technology Trends for 2019
Gartner Top 10 Strategic Technology Trends for 2020

Now after Shift Left / CI/CD, Automation tool companies are now looking how to bring intelligence in Test automation which can help in better test coverage and delivering quality at speed.

In this post, we will go over some intelligent features of Functionize and how they are using AI in bringing intelligence in automation and efficiency in Quality and Delivery.

Artificial intelligence ( Machine learning, Computer Vision & Natural language processing) can help in speeding up the automation test scripting, analysis and maintenance.

Below are some of the examples of how Functionize is using AI which helps in delivering Quality@Speed:

1. Faster test creation: Write tests in plain English (no, not Gherkin) and the framework with identify the objects by analyzing the DOM and perform actions. Example below:
   • Open xyz.com
   • Enter Username “abc”
   • Enter password “asdf123”
   • Navigate to Contact module.
   • Click in person record “Braidy”
2. Self Healing Scripts: Framework identifies the script failure reasons(due to change in object properties) and give your suggestions on fixing the scripts or fix the script by itself?
3. Autonomous Testing: All you need to do is – place a their tracking widget in your web app. Functionize will automatically create new test cases based on how live users interact with your site.

I am sure this short post will give you some ideas – how AI/ML can make our life easy and can help in delivering fast with quality.