Generative AI in Software Testing: How testRigor Generates Tests For You

How to use testRigor's Generative AI to generate actual end-to-end tests using testRigor. Use OpenAI GPT to generate real end-to-end tests.

The ever-changing technology landscape is continuously progressing, and Artificial Intelligence (AI) is playing an increasingly significant role in various aspects of our digital existence. AI is reshaping our interactions with the world, ranging from chatbots to recommendation systems. Quality Assurance (QA) is one area undergoing transformation through AI, particularly with the emergence of Generative AI.

Generative AI refers to systems that can generate novel, intricate, and tailored content. This concept originates from Machine Learning models trained on extensive data, enabling them to produce unique outputs based on user inputs. In the context of QA, this technology brings forth enhanced efficiency, accuracy, and effortless handling of large and intricate scenarios.

Now, consider the application of Generative AI to the creation of test cases. Imagine inputting a test case description, clicking a button, and witnessing the system rapidly crafting a comprehensive end-to-end test. This is no longer a hypothetical situation, thanks to the latest feature introduced by testRigor. And this video shows just that.

Benefits of Generative AI in QA
1. Reduction in Manual Labor
2. Increased Test Coverage
3. Consistency in Test Quality
4. Continual Learning and Improvement
5. Integration with Continuous Integration/Continuous Deployment (CI/CD) pipelines

Generative AI QA Use Cases
To demystify Generative AI in the context of QA, we can break it down into three primary use cases:
1. Generating examples based on a description
2. Code completion
3. Generating individual tests based on a description

#generativeaiinsoftwaretesting #generativeai #softwaretesting

[Kapriioza]

The testRigor platform itself makes automation easier. Using Generative AI will make it much more easier. Can't wait to try the new feature.

[testautomationtoolsblog]

Wow, this is truly groundbreaking! The power of Generative AI in software testing is evident in this impressive demonstration. Watching testRigor effortlessly create a full test scenario based solely on the test title "Find a Kindle and add it to the shopping cart" is mind-blowing. The way it comprehends the intent and automatically generates all the necessary steps to execute the test is a game-changer for the testing industry.

Automating test case generation with such precision and understanding is a significant advancement that promises to save an incredible amount of time and effort for QA teams. This technology has the potential to revolutionize the testing process, ensuring comprehensive test coverage while freeing up valuable resources for more critical tasks.

Kudos to the team behind testRigor for developing this remarkable product. I can't wait to see how Generative AI continues to shape the future of software testing, making it more efficient, reliable, and user-friendly. Exciting times ahead! 🚀🧠 #GenerativeAI #SoftwareTesting #testRigor #Innovation

[MinistryOfAutomation]

Thanks for posting this video, I am Lead SDET and curious to understand how your tool is working on claimed "Generative AI model" there is lot of things talked on the blog as well but still not clear how are you training your model ? how your test case creation is not limited only till adding a Kindle into the cart but going upto checkout (which was not asked initially) How much time/resources it tool to train the tool for such a simple test case generation ? Generative AI model takes time to learn and i believe someone (mostly QA) need to feed/work on such things before the tool gets trained on such models or application flow ? how much is that investment in terms of time and accuracy ?
How this is different than traditional record and playback feature in all other tools from years together ?
Will your tool is capable to work on complex workflows involved in ERP applications like Oracle, Workday or SAP ?
Can you generate test cases using such "generative AI" model on mathematical applications involved in finance industry or can this be used in medical software applications test case generation ?
Whats the ratio or percentage of accuracy of this model generating test cases as per user needs or feeded requirements ? There are so much unanswered questions here about all such tools which are claiming to use "Generative AI " for automated test case creation or fixing scripts automatically without any intervention but your target audience is "tester" so they are expected to test this kind of claims in and out before taking forward to management or even using it themselves so please provide in depth breakdown of the implementation and not just black box stuff to the market, thanks once again for helping the community with such innovation ! Looking forward to hear more.

[VijayGambhiraopet]

Quite impressive. Does it work for packaged applications? If not, can your model be trained?
And, can data be fed from an external source instead of being embedded?

[prasannadevi]

Hi @testRigor, Seems like the tool generates the functional tests and make our work muc easier. But is it possible to run API test using this suite?

[Nellorupeddareddy]

What about security, while we testing financial area. What about some edge case scenarios

[akashghorpade]

How can we train the model for specific to our app? How does this actually works? Please elaborate.

[pinkpantherguitar]

is it work on a non-english language website? (i mean if i type the prompts in english ofcourse)

[layefyg]

Does the tool supports the initial login process to a website? The website I want to test uses MagicLink authentication, so how would your tool work in this case?

[ticklegiggles]

@testRigor, How to use with jenkins and docker

[globalpromo]

It’s automating those test cases right?

[abhiuppal]

Can we train the tool for ETL testing for Azure cloud applications?

[debangamedhi]

Using test rigor we are testing only the implementation as per the dev. We should be testing against the requirements instead

[sheikarif]

wrapup Automation testers, its gonna reduce our jobs🤣

[alexzhukovsky]

Also, based on the above demo (and I am surprised to see that they even released this video to the general public) testRigor and Generative AI CLEARLY INCAPABLE of analyzing basic Shopping Cart form with pretty standard web elements such as Address text field, City text field, State dropdown, and Zip Code text filed, while identifying "Shopping Address" label as the most important web element to validate on the form (so if you re-run automation and only Shopping Address label is displaying and no other fields are showing up test will pass) and then failing to recognize the entire form by entering incomplete randomly generated address into one single text field shows how limited and stupid testRigor and Generative AI is.