Day2 QA2AI Generate API Tests(Python, Karate) Selenium UI for Swagger Data Testing Snowflake FoXYiZ скачать в хорошем качестве

Day2 QA2AI Generate API Tests(Python, Karate) Selenium UI for Swagger Data Testing Snowflake FoXYiZ

ITeLearn.com QA to AI training session that dives into modern challenges facing QA professionals, focusing heavily on API automation, large data handling, and the adoption of AI-driven tools. Key Discussion Points & Demonstrations: AI-Driven Automation Script Generation: We conducted a live demonstration using AI (specifically Cursor/LLM) to generate automation scripts for Swagger API endpoints. The AI successfully generated: Python Code using the requests library for robust API testing. Karate Scripts (DSL) for API testing. Selenium UI Tests designed to interact with the Swagger URL's clickable fields, achieving six UI tests passing on the swagger application. In total, the process yielded 60+ automated test scenarios. Data Testing and Large Datasets: We discussed the huge challenge of preparing test data when dealing with billions of records, data lakes, and junk data. The session introduced the concept of RAG (Retrieval Augmented Generation), noting that adding billions of records to a RAG system is difficult due to the limited context window of AI models, requiring data segmentation and categorization. Snowflake and AI Integration: The popularity of Snowflake was highlighted, especially in the UK. We noted the potential for solving problems in minutes using new features like AI/SQL command functions and semantic views, reducing the need to write pages of code. We also discussed the possibility of creating a course focusing on data testing and handling large data in enterprises, potentially using Snowflake. Low-Code/No-Code Automation with FoXYiZ: An exploration of the FoXYiZ framework, a low-code no-code solution that utilizes CSV files (for plans, actions, and test data/payloads) instead of traditional code. This framework achieves codeless execution and provides simple HTML and CSV reports. A comparison chart highlighted that FoXYiZ uses CSV files, requires no IDE, and is easy for non-coders, contrasting it with code-based tools like Python and Karate. AI Adoption and Strategy: We emphasized that while AI may reduce the number of jobs, QA professionals must be upgraded to survive in the market. For enterprise architects, putting ground rules, guardrails, and context in place is essential for effective use of organizational LLMs (like Chat GPT or Grok). The discussion also touched on the shift needed to link automation results with Jira stories or Confluence for comprehensive test coverage and completeness. We plan to continue project work and training, likely shifting the weekday session time to 9:00 a.m. Pacific till 17th October.