Day 5: Identify a case study on AI in testing and share your findings

We’re now on Day 5 of our 30 Days of AI in Testing challenge! Over the past few days, we’ve built foundational knowledge about AI in testing. Today, we’ll take a look at how our discoveries play out in real-world settings by exploring case studies or sharing personal experiences.

Task Steps

Option 1: Case Study Analysis

  • Search for a real-world example of where AI has been used to tackle testing challenges. This could be a published case study or an example shared in an article or blog post.

  • Select and analyse a case study that seems relevant or interesting to you. Make a note of the company and context, how AI was applied in their testing process, the specific AI tools or techniques used and the impact on testing outcomes/efficiency.

Option 2: Personal Experience Sharing

  • If you have personal experience with using AI tools or techniques in your testing activities, you can share your own journey and learnings.

  • Describe the context, the AI tools or techniques you used, how you applied them, and the outcomes or challenges you faced.

Share your Discoveries

  • Whether you choose Option 1 or Option 2, share your discoveries by replying to this post. Here are some prompts to guide your post:
    • Brief background on the case study or personal experience
    • How was AI used in their/your testing?
    • What tool(s) or techniques did they/you leverage?
    • What results did they/you achieve?
    • What stood out or surprised you about this example?
    • How does it relate to your own context or AI aspirations?

Why Take Part

  • See AI in Testing in Action: By exploring real-world examples, we gain insights into what’s possible and begin envisioning how AI could transform our own testing.

  • Deepen Your Understanding: By exploring a case study or personal experiences, you’ll gain a deeper appreciation for the complexity and nuance of integrating AI into testing workflows.

  • Share the Knowledge: Sharing your case study findings or personal experiences and discussing them with others offers a chance to learn from each other’s research, expanding our collective knowledge and perspectives on AI’s role in testing.

https://club.ministryoftesting.com/t/day-5-identify-a-case-study-on-ai-in-testing-and-share-your-findings/74458/1

My Day 5 Task

I recently read this article https://mp.weixin.qq.com/s/qxS6ty0tS1QDpIqPFNDseQ It’s a study and concrete demonstration of a ground-up solution for anomaly detection methods based on UI interaction intent understanding.

The article is in Chinese, so you can read it by translating it to English through software.

  1. Brief background on the case study or personal experience:
  • Meituan’s Store Platform Technology Department and Quality Engineering Department collaborated with Professor Zhou Yangfan’s team from Fudan University to develop a multimodal UI interaction intention recognition model and a corresponding UI interaction framework. As Meituan’s various business lines expanded and iterated, the task of UI testing became increasingly burdensome, leading to the development of this model.
  1. How Artificial Intelligence was used in their testing:
  • AI was utilized to fuse user-visible text, visual image content, and attributes in the UI component tree to accurately identify UI interaction intentions. This approach was taken to address the challenges of high manual costs in UI testing and the reliance on script testing for UI interaction functionality logic.
  1. Tools or Technologies Used:
  • The research used multimodal models that combine machine learning methods with image, text, and rendering tree information to understand and replicate the “cognition-operation-check” verification process that a tester would typically perform.
  1. Results Achieved:
  • The case study showed that test cases written based on UI interaction intentions demonstrated the ability to generalize across different platforms, apps, and technologies without the need for specific adaptations. The research has been accepted by ESEC/FSE 2023 (a top conference in the software field) and will be presented at their Industry track.
  1. What Impressed or Surprised You in this Example:
  • The article does not provide a personal impression or surprise factor; however, the innovative approach to UI interaction intention recognition and its application to create generalized test cases that can be reused across various apps and platforms is noteworthy.

About Event

The “30 Days of AI in Testing Challenge” is an initiative by the Ministry of Testing community. The last time I came across this community was during their “30 Days of Agile Testing” event.

Community Website: https://www.ministryoftesting.com

Event Link: https://www.ministryoftesting.com/events/30-days-of-ai-in-testing

Challenges: