The importance of quality assurance in software development cannot be overstated. With the progress of Artificial Intelligence (AI), the field of Quality Assurance is undergoing a transformation. This workshop aims to introduce practical ways to incorporate chatbots into Quality Engineers' daily tasks in order to improve efficiency and the overall quality of their work, but also to guide participants to come up with a variety of ways to utilize AI in their daily work.
The workshop will cover a range of topics, including explaining code, generating documentation from code, identifying edge case problems, automating test case generation, creating scripts to generate test data, implementing API tests, generating Cypress automation code, creating bug reports, troubleshooting and generating possible fixes from stack traces and more.
Participants will have the hands-on opportunity to try out these tasks using a test web application. The workshop incorporates a mix of theory and practice, with participants guided through the process of using AI in a range of real-world Quality Assurance tasks.
Participants are required to have familiarity with git, as they will need to clone the project beforehand and install all the dependencies using Node. The application to be tested will run on the participants' computers and will consist of a front-end interface and a backend API. Test automation will be done using Cypress. Deep knowledge of Cypress is not necessary, the project will be set up with initial tests and understanding them will be intuitive or with the help of AI.
To provide the AI chatbot an instance of Azure AI based on OpenAI's GTP-4 model will be provided. Participants do not require a ChatGPT subscription to access the chatbot.
This workshop is designed for those who already have basic technical knowledge to set up and run a local web application. It does not assume deep knowledge of quality assurance concepts but a familiarity with git, Node, and running a web application on their own device. While it's not a beginner course, the workshop aims to get the creative juices flowing regarding incorporating AI into daily tasks and could also be a great overview of different aspects in product's quality lifecycle for anyone.
Agenda for the day:
09:00 - 09:40: Introduction and Overview of the Workshop + technical setup: Set the stage for the day, introduce the agenda, and address any initial queries. Guide participants who have not done the setup of the project beforehand
09:40 - 09:55: Getting to Know the Field of the Project Under Test: Utilizing AI to dive into a field that is new for the participants.
09:55 - 10:30: Explaining What a Piece of Code Does: Discuss how AI can be used to understand and interpret code.
10:30 - 10:45: Break
10:45 - 11:15: Generate Documentation from Code: Demonstrate how AI can be used to generate documentation directly from code.
11:15 - 12:30: Finding Edge Case Problems: Dive deeper into how AI can identify edge cases and improve test coverage.
12:30 - 13:30: Lunch
13:30 - 14:00: Generating Test Cases: Discuss how AI can automate the generation of test cases.
14:00 - 14:30: Generating Scripts to Generate Test Data: Briefly show how AI can be used to generate scripts that create test data.
14:30 - 15:00: Generate Postman API Requests, Testing Edge Cases: Demonstrate how AI can generate API calls and tests, including those for edge cases.
15:00 - 15:15: Break
15:15 - 16:00 Generating Automation Code: See how AI can be used to generate automation code.
16:00 - 16:15: Generating Bug Reports: Test how AI can auto-generate detailed bug reports, saving time and improving the quality of reporting.
16:15 - 16:45: Troubleshooting, Generating Explanation and Possible Fixes from Stacktrace: Show how AI can analyze stack traces to identify the root cause of errors and suggest possible fixes.
16:45 - 17:00: Review of the Day and Conclusion of Workshop: Wrap up the day's activities, answer any remaining questions, and discuss how to apply the day's learning in real-world scenarios.
Key Takeaways:
- Attendees will gain a deeper understanding of how AI is transforming the field of Quality Assurance.
- Insights into how AI can be used to identify edge cases, generate test data, analyze logs, solve problems and automate the flow of testing.
- An inspired mindset to find more ways to apply AI to their daily tasks.
