10 publication(s), engineering notes, and curated picks tagged with #clean-code.
Why large switch statements age badly and how polymorphism helps contain the damage.
Examining the persistent divide between architectural ideals (Rich Domain Models, DDD, Clean Architecture) and real-world procedural production code.
How 3,700 AI credits, six false leads, and one unclosed mock taught me what 'flaky' really means in distributed test suites.
Bounded Contexts vs. Monolithic Global Database Schemas
Analyzing the divergence between relational database normalization (single shared global tables) and Domain-Driven Design (context-specific models where the same noun represents different entities across Bounded Contexts).
Agent pipelines, architecture boundaries, and timeless craftsmanship
Uncle Bob delivers a masterclass on how AI agents accelerate coding speed while proving that clean code, deep modules, deterministic verification, and fundamental engineering disciplines matter more than ever.
Behavior Before Function & Demystifying BDD vs. Acceptance Testing
Exploring why defining observable behavior must precede function implementation, while clarifying the distinction between writing .feature files as automated acceptance tests and practicing full collaborative BDD.
Goodhart’s Law, language idioms, and the pitfalls of software metrics
Kevlin Henney explores the language, terms, and mental models programmers use, explaining Goodhart’s Law and why software engineering metrics collapse when treated as control targets.
A foundational critique of object-oriented design and accidental complexity
Brian Will makes a structured, provocative case against OOP, arguing that combining state and behavior into encapsulation graphs produces rigid webs of mutation, complex patterns, and maintenance overhead.
Cost of Change (CoC) economics, technical debt curve, and core design smells
A dense, high-value visual reference mapping out why clean code keeps the Cost of Change constant over time, alongside definitions for the 8 core architectural smells.
Why default JPA repository query methods degrade enterprise database throughput
A deep technical examination of why extending Spring Data’s default findAll() in entity repositories leads to memory bloat, unindexed table scans, and N+1 query storms.
