惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

WordPress大学
WordPress大学
Cyberwarzone
Cyberwarzone
The GitHub Blog
The GitHub Blog
云风的 BLOG
云风的 BLOG
P
Proofpoint News Feed
小众软件
小众软件
Recent Announcements
Recent Announcements
博客园 - 三生石上(FineUI控件)
Security Archives - TechRepublic
Security Archives - TechRepublic
W
WeLiveSecurity
Cloudbric
Cloudbric
博客园 - 司徒正美
美团技术团队
N
News and Events Feed by Topic
Exploit-DB.com RSS Feed
Exploit-DB.com RSS Feed
PCI Perspectives
PCI Perspectives
宝玉的分享
宝玉的分享
H
Help Net Security
H
Hackread – Cybersecurity News, Data Breaches, AI and More
Google DeepMind News
Google DeepMind News
Help Net Security
Help Net Security
Last Week in AI
Last Week in AI
S
Schneier on Security
N
News | PayPal Newsroom
B
Blog RSS Feed
L
LINUX DO - 最新话题
T
Troy Hunt's Blog
S
Secure Thoughts
雷峰网
雷峰网
aimingoo的专栏
aimingoo的专栏
L
Lohrmann on Cybersecurity
G
Google Developers Blog
Microsoft Azure Blog
Microsoft Azure Blog
Hacker News - Newest:
Hacker News - Newest: "LLM"
T
Tenable Blog
S
Securelist
L
LangChain Blog
Recent Commits to openclaw:main
Recent Commits to openclaw:main
I
InfoQ
H
Heimdal Security Blog
Cisco Talos Blog
Cisco Talos Blog
F
Full Disclosure
Y
Y Combinator Blog
酷 壳 – CoolShell
酷 壳 – CoolShell
K
Kaspersky official blog
T
Tailwind CSS Blog
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
阮一峰的网络日志
阮一峰的网络日志
C
Cisco Blogs

DEV Community

Authentication Security Deep Dive: From Brute Force to Salted Hashing (With Java Examples) Why AI Systems Don’t Fail — They Drift Spilling beans for how i learn for exam😁"Reinforcement Learning Cheat Sheet" I Replaced Chrome with Safari for AI Browser Automation. Here's What Broke (and What Finally Worked) How Python Borrows Other People's Work The $40 Architecture: Processing 1 Billion API Requests with 99.99% Uptime Vibe Coding: A Workflow Guide (From Zero to SaaS) Most webhook security guides protect the wrong side. The scary part is delivery. Headless CMS for TanStack Start: Build a Blog with Cosmic EU Age Verification App "Hacked in 2 Minutes" — What Actually Happened Comfy Cloud’s delete function does not actually remove files Running AI Models on GPU Cloud Servers: A Beginner Guide Event-driven media intelligence with AWS Step Functions and Bedrock I scored 500 AI prompts across 8 quality dimensions — here's what broke How to Call Google Gemini API from Next.js (Free Tier, No Backend Needed) The Portal Protocol: Reclaiming Human Connection in the Age of AI How to Fix Your Team's Scattered Knowledge Problem With a Self-Hosted Forum Intro to tc Cloud Functors: A Graph-First Mental Model for the Modern Cloud Designing Multi-Tenant Backends With Both Ownership and Team Access I Built a Neumorphic CSS Library with 77+ Components — Here's What I Learned PostgreSQL Performance Optimization: Why Connection Pooling Is Critical at Scale Cómo construí un SaaS multi-rubro para gestionar expensas en Argentina con FastAPI + Vue 3 🚀 I Built an Ethical Hacking Scanner Tool – Open Source Project I Replaced /usage and /context in Claude Code With a Single Statusline A Pythonic Way to Handle Emails (IMAP/SMTP) with Auto-Discovery and AI-Ready Design I Collected 8.9 Million Polymarket Price Points — Here's What I Found About How Markets Really Move EcoTrack AI — Carbon Footprint Tracker & Dashboard Everyone's Using AI. No One Agrees How. 5 self-hosted ebook managers worth trying in 2026 Building Your First AI Agent with LangChain: From Chatbot to Autonomous Assistant Common SOC 2 Failures (Real World) Stop Vibe-Checking Your AI App: A Practical Guide to Evals How to Use SonarQube and SonarScanner Locally to Level Up Your Code Quality Your Next To-Do App Is Dead — I Replaced Mine with an OpenClaw AI Sign a Nostr event in 60 lines of Python using coincurve — no nostr-sdk, no nbxplorer, no rust toolchain ITGC Audit Explained Like You’re in Big 4 Patch Tuesday abril 2026: Microsoft parcha 163 vulnerabilidades y un zero-day en SharePoint Stop scraping everything: a better way to track competitor price changes Listing on MCPize + the Official MCP Registry while routing payments OUTSIDE the marketplace — how I kept 100% of my x402 revenue Building an AI-Powered Risk Intelligence System Using Serverless Architecture Why We Ripped Function Overloading Out of Our AI Toolchain Testing AI-Generated Code: How to Actually Know If It Works SaaS Churn Is Killing Your Business. Here Is What to Do About It (Without a Support Team) The Speed of AI Is No Longer Linear - And Self-Improving Models Are Why How to Implement RBAC for MCP Tools: A Practical Guide for Engineering Teams From Standard Quote to Persuasive Proposal: AI Automation for Arborists I built a CLI that scaffolds complete multi-tenant SaaS apps Axios CVE-2025–62718: The Silent SSRF Bug That Could Be Hiding in Your Node.js App Right Now The dashboard that ended our friendship Data Pipelines Explained Simply (and How to Build Them with Python) The Hidden Cost of AI Systems Nobody Talks About. undefined vs undeclared, and how typeof behaves Switching from file-based jobs to NATS/Kafka in Rust without changing code io_uring Adventures: Rust Servers That Love Syscalls Why Agentic AI is Killing the Traditional Database The POUR principles of web accessibility for developers and designers Quantum Neural Network 3D — A Deep Dive into Interactive WebGL Visualization How To Install Caveman In Codex On macOS And Windows Automation Pipeline Reliability: Why Your Workflow Breaks When Nobody Is Watching I Built an 'Open World' AI Coding Agent — It Works From ANY Folder From Freelancing to Product: A Tech Service Company's SaaS Transformation China's AI Giants: Adding Tencent Hunyuan & ByteDance Doubao to AI University (74 Providers) On the Vibe Coders and Their Lies clerk: Auto-Summarize Your Claude Code Sessions AI Weekly — 2026/04/10–04/17 | The Model Lockdown Is Here, but the Toolchain Is the Real Battleground AI 週報 — 2026/04/10–2026/04/17 模型封鎖潮來了,但工具鏈才是真戰場 Maybe this is how Open-Source apps are born... 🚀 Fine-Tune LLMs with LoRA and QLoRA: 2026 Guide tRPC v11 + Next.js App Router: End-to-End Type Safety Without the Boilerplate ShadCN UI in 2026: Why I Stopped Installing Component Libraries and Started Owning My Components SaaS Billing in React Server Components: Stripe + Supabase Without a Single `useEffect` Join our DEV Weekend Challenge — $1,000 in Prizes Across TEN winners! Submissions Due April 20 at 6:59 AM UTC. Implementing FSRS Spaced Repetition in Flutter + Supabase — Adding Memory Science to an AI Learning App "I Texted My Localhost From the Train — Claude Code Fixed the Bug Before I Got Home" I Built a Sales Prep AI and It Went Deeper Than Expected Design to Code #2: One JSON, Eleven Outputs Solving the 100M-Row Problem: A Summary Table Pattern for High-Volume Push Notification Logs Flutter Web With Wasm: What Actually Changes For Developers I Built 50 Royalty-Free Soundtracks for My Side Project in a Weekend Using AI Music Generation The Vibe Coding Security Checklist: 7 Things to Check Before You Ship Stop Letting Googlebot Guess Fix Your React App's SEO Right Desconstruindo o Streaming do LinkedIn: Como Criar um Engine de Extração de Vídeo de Alta Performance com HLS e FFmpeg (EDA Part-1) EDA (Exploratory Data Analysis) Explained With Real Life — Why Looking at Your Data Is the Most Important Step in Machine Learning Brand Relationship Management at Scale: Our 4-Touch Outreach System for 200+ Brands Why String.fromEnvironment() Might Return an Empty String in Dart JGuardrails 1.0.0 — Hardening Java LLM Apps Against Jailbreaks, Toxicity, and Prompt Injection Plan and Schedule a Full Week of Threads Content From One Claude Conversation Coding Cat Oran Ep3, Five Tables Changed Everything Updated: BFF Pattern I'm done watching freelancers get buried by 200 proposals. So I'm building the alternative. This is my first post BFS Algorithm in Java Step by Step Tutorial with Examples Tracking LLM Pricing Monthly: An Open Dataset for 22 AI Models How We Measure Content ROI on a Comparison Site: Revenue Attribution Without Perfect Data Introducing Nova AI Ops: The AI-Native Operating System for SRE Teams I built a free desktop video downloader for Windows — Grabbit How Talkie OCR Helps Vision-Impaired & Dyslexic Users Read the World Around Them VRCFaceTracking安装和iPhone面捕配置教程,有bug Even CrowdStrike Can't See Your Agents The Automation Gold Rush: What n8n Workflows and Claude Are Opening Up for Developers Right Now
Testing AI-Powered Applications: Strategies for LLM Integration
ZNY · 2026-05-16 · via DEV Community

Testing AI applications is fundamentally different from testing traditional software. There's no deterministic output, prompts change behavior, and edge cases multiply. Here's how to build a robust testing strategy for AI-powered applications.

The AI Testing Challenge

Traditional testing:

Input → Function → Expected Output

AI testing:

Input → Prompt + Context → Probabilistic Output

You can't assert exact outputs. Instead, you test properties.

Property-Based Testing for AI

`typescript
// Instead of testing exact output, test properties

interface TestCase {
input: string;
constraints: Constraint[];
}

interface Constraint {
type: 'contains' | 'excludes' | 'length' | 'format' | 'json';
value: string | number | RegExp;
}

async function testAIOutput(testCase: TestCase, actualOutput: string): Promise {
for (const constraint of testCase.constraints) {
switch (constraint.type) {
case 'contains':
if (!actualOutput.includes(constraint.value as string)) return false;
break;
case 'excludes':
if (actualOutput.includes(constraint.value as string)) return false;
break;
case 'length':
if (actualOutput.length > (constraint.value as number)) return false;
break;
case 'json':
try {
JSON.parse(actualOutput);
} catch {
return false;
}
break;
}
}
return true;
}

// Example test
const testCase: TestCase = {
input: 'Extract the name and email from: John Doe, john@example.com',
constraints: [
{ type: 'contains', value: 'John' },
{ type: 'contains', value: 'john@example.com' },
{ type: 'excludes', value: 'undefined' },
{ type: 'length', value: 100 }
]
};
`

Prompt Versioning and Regression Testing

`python
import hashlib
from datetime import datetime

class PromptRegistry:
def init(self):
self.prompts = {}

def register(self, name: str, version: str, prompt: str, test_cases: list):
key = f"{name}:{version}"
self.prompts[key] = {
'prompt': prompt,
'testcases': testcases,
'hash': hashlib.md5(prompt.encode()).hexdigest(),
'registered': datetime.now()
}

def get_prompt(self, name: str, version: str) -> str:
return self.prompts[f"{name}:{version}"]['prompt']

def regressiontest(self, name: str, newversion: str,
llm_client, threshold: float = 0.8) -> bool:
"""Ensure new version passes existing test cases."""
old_prompt = self.prompts.get(f"{name}:{version}")
if not old_prompt:
return True

old_passes = 0
new_passes = 0

for tc in oldprompt['testcases']:
oldresult = await llmclient.complete(old_prompt['prompt'] + tc['input'])
newresult = await llmclient.complete(
self.getprompt(name, newversion) + tc['input']
)

oldok = await testAIOutput(tc, oldresult)
newok = await testAIOutput(tc, newresult)

if oldok: oldpasses += 1
if newok: newpasses += 1

New version should pass at least as many tests

return (newpasses / len(oldprompt['test_cases'])) >= threshold
`

Deterministic Output Testing

For structured outputs, test deterministically:

`typescript
import { z } from 'zod';

const CodeReviewSchema = z.object({
score: z.number().min(0).max(10),
issues: z.array(z.object({
severity: z.enum(['low', 'medium', 'high']),
line: z.number(),
description: z.string()
})),
summary: z.string()
});

async function testCodeReview(code: string, expectedScoreRange: [number, number]) {
const response = await llm.complete(
Review this code and return JSON: ${code}
);

// Parse and validate
const parsed = JSON.parse(response);
const validated = CodeReviewSchema.parse(parsed);

// Deterministic assertions
console.assert(
validated.score >= expectedScoreRange[0] &&
validated.score <= expectedScoreRange[1],
Score ${validated.score} outside expected range
);

console.assert(
validated.issues.length < 20,
'Too many issues reported'
);

return validated;
}
`

Mocking External AI Calls

`typescript
// For unit tests, mock the LLM client
class MockLLMClient {
constructor(private fixtures: Map) {}

async complete(prompt: string): Promise {
// Return fixture matching prompt pattern
for (const [pattern, response] of this.fixtures) {
if (prompt.includes(pattern)) {
return response;
}
}
return 'Mock response';
}

async *stream(prompt: string): AsyncGenerator {
const response = await this.complete(prompt);
for (const char of response) {
yield char;
}
}
}

// Usage in tests
const mockClient = new MockLLMClient(new Map([
['extract email', '{"email": "test@example.com"}'],
['summarize', 'This is a summary of the text.']
]));

// Now your business logic tests run fast and deterministically
`

Chaos Testing for AI Applications

`python
class AIChaosTests:
def testratelimits(self, client):
"""Does your app handle rate limits gracefully?"""
for _ in range(100):
try:
client.complete("test")
except RateLimitError:
assert client.retry_count > 0
break
else:
pytest.fail("Rate limit not encountered after 100 requests")

def testinvalidjson(self, client):
"""Does your app handle malformed JSON from LLM?"""

Inject bad response

client.mock_response('{"broken": }')
result = safeparsejson(client.complete("test"))
assert result is not None # Handled gracefully

def testemptycontext(self, client):
"""Does your app handle empty context?"""
result = client.complete("")
assert result is not None

def testmaxtokens_respected(self, client):
"""Does max_tokens actually limit output?"""
result = client.complete("test", max_tokens=10)
assert len(result) <= 50 # ~10 tokens
`

Integration Test Framework

`typescript
describe('AI Integration Tests', () => {
const client = new ClaudeClient(process.env.OFOXAPIKEY);

describe('Code Review Feature', () => {
it('identifies syntax errors', async () => {
const code = 'const x = ;';
const review = await reviewCode(client, code);
expect(review.issues.some(i => i.severity === 'high')).toBe(true);
});

it('handles valid code gracefully', async () => {
const code = 'const x = 42;';
const review = await reviewCode(client, code);
expect(review.issues.filter(i => i.severity === 'high')).toHaveLength(0);
});

it('respects max issues limit', async () => {
const code = '...'; // Large code
const review = await reviewCode(client, code, { maxIssues: 10 });
expect(review.issues.length).toBeLessThanOrEqual(10);
});
});
});
`

Building Testable AI Systems

  1. Separate concerns — Keep prompts in config, not buried in code
  2. Structured outputs — Use Zod/JSON Schema to constrain responses
  3. Fallback handling — Plan for API failures at every call site
  4. Snapshot testing — Store expected responses for regression

Getting Started

Build testable AI applications with ofox.ai — their API is reliable and consistent, making it easier to build deterministic test suites.

👉 Get started with ofox.ai

This article contains affiliate links.

Tags: testing,ai,programming,developer,quality
Canonical URL: https://dev.to/zny10289