DDD、SDD、TDD:三個維度的邊際效益矩陣
軟體團隊常把 DDD、SDD 與 TDD 當成三選一的方法論,但它們其實分別處理領域語言、介面契約與重構風險。本文用三軸矩陣拆解三者在不同複雜度、協作邊界與變更成本下的邊際效益,提供判斷何時投資建模、規格或測試的實用框架,避免把方法論討論變成宗教戰爭。
軟體團隊常把 DDD、SDD 與 TDD 當成三選一的方法論,但它們其實分別處理領域語言、介面契約與重構風險。本文用三軸矩陣拆解三者在不同複雜度、協作邊界與變更成本下的邊際效益,提供判斷何時投資建模、規格或測試的實用框架,避免把方法論討論變成宗教戰爭。
DDD, SDD, and TDD address different risks: domain language, interface contracts, and change safety. This matrix shows where each method pays off.
AI wrote 200 tests for me. All passed. We deployed. Then a bug hit production. The problem wasn’t that AI wrote bad tests—it tested the wrong things. This article shares a simple framework: What stays with humans, How goes to AI.
AI 幫我寫了 200 個測試,全部通過,上線還是出 bug。問題不是 AI 寫錯,是它測的東西根本不是該測的。這篇文章分享一個簡單的框架:What 留給人,How 交給 AI。
AI excels at executing tests, but struggles with judging ‘what to test’ and ‘whether results are correct.’ QA’s core value is shifting from execution to acceptance—validating AI’s validation. This article analyzes the four most important QA skills in the AI era and the short, medium, and long-term impacts on teams.
AI 擅長執行測試,但不擅長判斷「該測什麼」和「結果對不對」。QA 的核心價值正在從執行轉向驗收——驗證 AI 的驗證。本文分析 AI 時代 QA 最重要的四種能力排序,以及對團隊的短中長期影響。
深度解析如何利用 LangChain4j、GPT-4o 與 Playwright 打造 AI 測試代理人。本文詳細探討在缺乏文檔的大型 Java 遺留系統中,如何透過「探索、診斷、穩定性」三重迴圈機制,實現超越傳統自動化的自主驗收測試,並提供完整的實作代碼與導入路線圖。
A complete technical implementation plan: Building an AI Testing Agent using LangChain4j, GPT-4o, and Playwright. Includes full code concepts, prompt engineering, state machine architecture, CI/CD integration, and a concrete adoption roadmap.
Master E2E Testing: Debunk the ‘Ice Cream Cone’ anti-pattern, leverage AI visual regression, and build reliable Playwright strategies for confident deployments.
E2E 測試完全指南。破解 200 個購物車測試案例的迷思,深入解析 AI 視覺回歸與自我修復技術。學習如何結合 Playwright 與單元測試,建立高信心的自動化防護網。