AI testing leverages automated tools using artificial intelligence to improve software testing efficiency and effectiveness, with a projected industry value of $190 billion by 2025. It addresses challenges such as test execution speed, maintenance, and quality by utilizing machine learning for creating and managing test cases. Key tools include Difblue Cover for unit tests, FBInfer for source code analysis, and Testim Automate for automation, all designed to streamline the testing process.

1. AI Testing: What, Why &
How To Do It?

2. AI Testing: What Is It?
To produce better results, AI testing
uses automated software tools that use
artificial intelligence (AI), typically
machine learning. These apparatuses
can defeat many of the normal obstacles
of computerized programming testing.

3. Key Statistics
6.83% of firms
believe AI is a
strategic emphasis
for their business.
61% of business
owners use artificial
intelligence as their
organization’s most
crucial data-driven
endeavours.
By 2025, the AI
testing industry will
be a $190 billion
industry.
By using AI testing,
businesses can
increase their
productivity by
40%.
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4. AI Testing: Why To Use?
1.Test Execution
A test suite that takes a long to run is different from
what anyone wants. There are several ways that AI
testing tools can ease that pain.
2. Excessive Test Upkeep
Using machine learning to develop a more sophisticated
strategy for locating elements on the page and producing
more robust tests, an AI-powered tool like Testim
Automate can address this issue.
3. Superior Quality Test Cases
By locating existing, reusable components that can be
called rather than duplicated,AI testing tools can generate
test cases at the unit and even API levels.

5. 4. Efforts to Test Waste
Test cases with a known and proven reusable group can
help ensure your test case completes consistently.
5. Test Coverage
AI testing tools may identify, remove, or skip low test
cases during execution by identifying and creating new
cases by analyzing previous exploratory testing sessions
to ensure greater coverage.

6. AI Testing: How To Do It?
Let’s look at some AI-powered tools to
start your AI testing journey.

7. 1. Difblue Cover
It is an AI tool for creating unit tests with Java code. It is
available as a CLI tool and a plugin for IntelliJ IDEA. It looks
over your code and creates unit tests consistent with what
you’ve implemented.
2. FBInfer
It is a static analysis tool that uses artificial intelligence to
find potential flaws in the source code before it is shipped
to production. It’s shift left testing at its best.
3. Testim Automate
It is a test automation platform that uses machine learning
to address two of software testing’s most persistent
issues: high test maintenance and slow test authoring.