AI testing
# Bridging AI Evaluation with Real-World Business Impact *Magdalena Picariello reframes AI conversations around measurable business value, iterative development, and feedback-driven optimization.* --- ## Introduction Magdalena shifts focus from **algorithms and metrics** to **tangible business outcomes**, advocating for evaluation systems that go beyond accuracy. Her approach: - **Continuous feedback loops** - **Iterative
AI testing
# **Article #121 of 2025** *(Estimated reading time: 15 minutes)* --- ## **01. Background** ### **1.1 Industry Analysis & Reflection** With the rapid evolution of large models, the testing industry is exploring **AI-assisted approaches** for various QA scenarios. In **agent generation**, most solutions rely on the **Prompt + RAG** (Retrieval-Augmented Generation) pattern to
AI testing
Tmall AI-Enabled Testing Practice: Intelligent Test Case Generation --- Introduction This article details the Tmall Technology Team’s exploration and implementation of AI-powered intelligent test case generation, providing a step-by-step methodology and practical insights. --- 1. Background 1.1 Industry Analysis & Insights With large language models (LLMs) advancing rapidly,
AI testing
AI-Powered Transformation in Tmall’s Testing Workflow Article No. 118 (2025) Estimated read time: 15 minutes --- Tmall’s quality assurance engineers are leveraging AI to revolutionize the five core testing stages: > Requirement Analysis → Test Case Generation → Data Construction → Execution & Verification → Comparison & Validation The vision is end-to-end
JavaScript testing
# As a Software Engineer, Always Embrace the Challenges Two months ago, my project manager assigned me a task: **write test cases for an API**. I was genuinely excited because it meant learning something new beyond just building features. If you’re thinking *“writing test cases isn’t my job as