Android App Automation: Frameworks, Setup and CI
Android app automation with Espresso, UI Automator, Appium and Maestro: compare frameworks, write a first test, pick emulators or real devices, and run in CI.
Stories from Testmuai
Use this page to scan recent stories from Testmuai, see the themes that keep appearing, and jump into complete story briefs.
Recurring themes in this source.
Mobile App TestingAutomationAIAI TestingTestingSecurityAgent Testing
Recent curated reads
G-Eval: How It Scores LLM Output, and What Its Data Shows
G-Eval scores LLM output with model-written evaluation steps and a probability-weighted score. See how it works, a recount of its SummEval data, and its limits.
Agent-as-a-Judge: How Agent Judges Grade What AI Agents Did
Agent-as-a-judge uses an AI agent with tools to grade another agent's work. Compare it with LLM judges and see a recount of the DevAI judges' error direction.
What Is a Golden Dataset? How to Build, Size and Version One
A golden dataset is a reviewed, versioned set of real inputs an AI system is scored against on every change. Learn how to build, size, version and refresh one.
Ecommerce Testing: Types, Test Cases, Checklist and Tools
Ecommerce testing checks the purchase funnel end to end. Learn the test types, 13 funnel test cases, a 9-step process, a verified Playwright example, and tools.
What Is AI Security? Risks by Layer, Frameworks and Testing
What is AI security? Learn how to secure AI data, models, apps, agents and infrastructure, which frameworks apply, how to test, and where AI flaws come from.
AI Agent Simulation: Simulated Users, Personas and Scoring
AI agent simulation tests an agent with simulated users in full conversations. Learn the run anatomy, persona design, suite sizing, scoring and its limits.
Groundedness in AI: What It Measures and How It Is Scored
Groundedness checks whether each claim in an AI answer is supported by its sources. Learn how scores are calculated, why tools disagree and what they miss.
Bug Tracking: A Complete Guide for Developers and Testers
A complete guide to bug tracking and issue tracking: key processes, the defect life cycle, top tools, and best practices to manage issues for QA and dev teams.
HumanEval Benchmark: 164 Problems, pass@1 and HumanEval+
The HumanEval benchmark scores code models on 164 Python problems by pass@1. See how its tests accept wrong code, what HumanEval+ adds and why it is saturated.
MMLU Benchmark: 57 Subjects, Label Errors and Score Margins
The MMLU benchmark tests models on four-option questions in 57 subjects. See per-subject question counts and margins, label errors, variants and top scores.
Jailbreak AI: How LLM Jailbreaks Work and How to Test Them
Jailbreak AI explained: how LLM jailbreak techniques work, what public JailbreakBench data shows about attack success, and how to test your AI apps and agents.
Read this source in the app
Open the app view when you want faster scanning, saved stories, and source-focused reading in one place.