Generative AI in Application Testing

Since 2022, Generative AI has taken over the world by a storm. Generative AI has been transforming the way world works. From generating images, texts, videos to transforming business operations, Generative AI is at the dawn of its time. The use cases of generative AI are just at the brink of beginning a chain reaction of digital transformation in several industries & business units.

In the Information Technology space this transformation is rapidly being embraced & as the space is acting as a change agent for other sectors, the IT space is also getting transformed.

With Generative AI, the entire journey from ideating to closure, including the software development itself is being transformed. This paper focuses on “How Generative AI is transforming the software testing & related aspects of Quality Assurance.

The 1-10-100 rule states that “It makes more sense to invest $1 in prevention than to spend $10 on the correction. That, in turn, makes more sense than to incur the cost of a $100 failure”. This rule quite applicable in software testing.

Software testing can be enhanced with GenAI in 2 ways

1. Creating intricate test cases & scenarios, helping the testers to rather focus on test execution aspect &
2. Creating test artifacts

One of the obvious ways is to create a private supervised learning LLM model that would be explicitly trained on business case specific data & reap the benefits by using this model for reducing the manual efforts of tester.

Alternatively, existing generative AI models such as ChatGPT can be used to create a private model using the powerful LangChain framework for developing applications powered by the LLMs.

Using LangChain, creating a context aware & reason-based solution that is specifically trained on data set that we are interested to teach the model.