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Responsible Usage of AI in Testing
Responsible Usage of AI in Testing

Quickly learn about the best practices in using AI while testing

Zorica Micanovic avatar
Written by Zorica Micanovic
Updated over 9 months ago

The Definition of AI

AI (Artificial Intelligence) is a field of computer science that involves creating algorithms and systems that enable machines to mimic human intelligence. This technology is employed to create smart systems and robots capable of performing tasks that would require human intelligence, such as interpreting visual images, recognizing speech, decision-making, and translating between languages.

General Usage

In the technology landscape, the use of AI has become very prevalent due to its myriad possible applications. Its ability to analyze and interpret complex data, predict outcomes with greater accuracy, automate repetitive tasks, and improve efficiency has revolutionized various industries such as healthcare, finance, entertainment, transportation, marketing, and so forth. Additionally, it has a significant role in improving customer satisfaction by allowing the creation of personalized communications and predictive responses.

AI Potential in Manual Functional Testing

AI has proven to be a game-changer in the field of software testing, offering a new approach to manual functional testing. Good prompt can create a user flow path that can help newbies channel their testing to some specific areas based on the scope.

Let's see an example of the prompt and the response from AI.

Hello, ChatGPT! Can you help me create the user flow for manual functional testing of the e-commerce website that has the following features: Homepage, Account, Wishlist, Product Overview Page, Product Detail Page, Cart, Checkout, Newsletter, Footer, and Header? Also, make sure that placing orders is out of scope. Testers are not allowed to place any orders while they are allowed to proceed to the Checkout. Bug types that are in the scope of the test are Functional (Low, High, and Critical), Content, and Visual. 

With a prompt like this, you don't give AI any data about the customer or any other specifics from the test cycle.

Now, let's see the response from the AI.

Sure. In that case, the user flow would look like this:

1. Homepage:
- Check if all the graphics, images, and texts load properly on the Homepage.
- Ensure that clickables (buttons, dropdowns, sliders) are functional.

2. Header and Footer:
- Test that all the links in the header & footer are directed to the correct page.
- Check if the company logo redirects to the home page.
- Verify the contact information and social media links working properly.
- Check if all the graphics, images, and texts load properly.

3. User Account:
- Test the functionality of creating a new account.
- Confirm if the form accepts/rejects valid/invalid email addresses.
- Check the login function with the correct/incorrect username and password.
- Test for recovering the forgotten password.
- Verify the editing functionality in account details - change password, change email, and delivery address.
- Check if all the graphics, images, and texts load properly.

4. Newsletter:
- Confirm the subscription and unsubscription functionality.
- Confirm if the form accepts/rejects valid/invalid email addresses.
- Check if all the graphics, images, and texts load properly.

5. Product Overview Page:
- Ensure that all products are displayed accurately with correct descriptions and prices.
- Check the function of the filter and sort on the page.
- Verify the 'Add to Cart' and 'Add to Wishlist' buttons functioning properly.
- Check if all the graphics, images, and texts load properly.

6. Product Detail Page:
- Verify that each product detail page correctly portrays the product image, price, description, specifications, and customer reviews if available.
- Ensure the 'Add to cart' and 'Add to wishlist' functionality is working as expected.
- Check if all the graphics, images, and texts load properly.

7. Wishlist:
- Check the functionality to add/remove items from the Wishlist.
- Verify the functionality to move Wishlist items to the Shopping Cart.
- Check if all the graphics, images, and texts load properly.

8. Shopping Cart:
- Verify the function of adding, updating, and removing products from the cart.
- Check updates in the total price with changes in the products in the cart.
- Check if all the graphics, images, and texts load properly.

9. Checkout Process:
- Test entering delivery addresses and selecting delivery options.
- Proceed to the payment gateway process but do not complete the order.
- Check if all the graphics, images, and texts load properly.

10. General:
- Check on various devices & browsers (cross-browser test and mobile responsive check).


Keep in mind that testers are not allowed to place any orders, hence actual transactions should not be performed.

Important: Based on the test instructions, feature descriptions, and OOS section, the prompt must be edited for the best possible results of the output. If you still wonder if the strategy given by the AI complies with the test cycle scope, reach out to the test cycle TL for help.

However, Test IO testers need to keep in mind that AI should not replace human judgment. The combination of AI's data-driven insights with human testers' intuition and creativity is crucial to a comprehensive testing process.

AI Traps

Despite the many benefits of AI, it also carries potential risks. One significant concern is data privacy. Many AI algorithms demand extensive data to function effectively, and this can lead to misuse and data breaches if not handled correctly. A particular example is when Test IO testers use AI as part of their test strategy. They must ensure that no sensitive, confidential, or any other customer data is shared with AI.

Conclusion

Thus, while AI has immense potential in multiple domains, including manual testing, it's crucial to remember the importance of ethical usage. Missteps can lead to loss of trust and legal issues. With responsible use of the technology, manual testing can be significantly upgraded, leading to more robust, efficient, and user-friendly system implementations. Ultimately, AI is a tool that should augment, not replace, human testers' expertise, potential, intuition, and ethics.

Moreover, AI's predictions are only as good as the data it's fed.

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