Category: System Design

A complete guide to the Composition Over Inheritance design principle: the LEGO-and-costume-shop analogy, the formal definition and its Gang of Four origins with a fair acknowledgment of the original nuance, the fragile base class problem illustrated with the classic Bird-Penguin example, a full has-a versus is-a comparison, a step-by-step build of a Bird class using swappable FlyBehavior and SoundBehavior interfaces (essentially Strategy pattern), a five-row comparison table, real-world examples across Unity components, Go, React, and Strategy/Decorator patterns, honest strengths and trade-offs, when inheritance still makes sense (with a Shape-Polygon-Rectangle-Square depth warning), common pitfalls (composing everything, deep composition chains, forgetting interfaces, treating the preference as an absolute rule), and a quick tour across Java/C#, Go, Python, and Rust.

A complete guide to the Spaghetti Code anti-pattern: the tangled-plate-of-spaghetti analogy, the formal definition (tangled control flow, structure not correctness), the historical origin in the GOTO instruction and Dijkstra 1968 letter “Go To Statement Considered Harmful,” the four common causes (deadline pressure, no upfront design, many hands without coordination, missing refactoring time), the six warning signs (deep nesting, long functions, unpredictable jumps, shared global state, copy-paste duplication, no clear sections), a step-by-step walkthrough of a processOrder function tangling from 4 lines into 7-level nesting and back out through extract-function refactoring, comparisons with God Object / Big Ball of Mud / Lava Flow / Shotgun Surgery, real-world examples (legacy enterprise, startups, student projects, research code), honest short-term convenience vs. long-term cost, detection techniques (cyclomatic complexity, nesting depth, static analysis, the “explain out loud” test), and a five-step untangling plan.

A complete guide to Dependency Injection (DI) as a software design principle: the lamp / bulb / socket analogy, its formal definition and relationship with Inversion of Control, the tight-coupling problem it solves (with a before / after order-confirmation example), the three roles involved (Client, Service, Injector), a step-by-step build in pseudocode showing how the same class powers both production and testing, the three injection styles (constructor / setter / interface), real-world examples across Spring, .NET, Angular, Hilt/Dagger, honest strengths and trade-offs, when to use it and when not to, common pitfalls like Constructor Overload and Service Locator confusion, and a quick tour across major languages and frameworks.

Both promise a set of actions before any details are filled in. Both stop you from creating an object directly from them. So why do object-oriented languages bother offering both? This thirteen-chapter guide unpacks what each one really is, five side-by-side differences, a small Vehicles-and-Rechargeable code example, whether a class can use both at once (yes — and it is common), why languages offer both instead of just one, four steps for choosing between them, pros and cons of each, common pitfalls, everyday examples from media apps to smart homes, an FAQ, and a six-line takeaway.

Four ideas hold up almost every large piece of software you have ever used — encapsulation, abstraction, inheritance, and polymorphism. They sound technical, but underneath, they are just clever ways of organising things. This twelve-chapter guide walks through what OOP itself really is, the difference between classes and objects, each of the four pillars in depth (with a Python example, an analogy, and a “why it matters” callout for each), how they cooperate in a game full of knights and wizards, an honest look at the pros and cons of OOP, common pitfalls, everyday examples from banking apps to media players, an FAQ, and a six-line takeaway.

Why write the same thing twice when one class can simply borrow it from another? Inheritance lets related pieces of code share what they have in common — while each one still keeps what makes it special. This thirteen-chapter guide walks through what inheritance really is, the “is-a” relationship, how it actually works in Python, the five recognisable shapes (single, multilevel, hierarchical, multiple, hybrid) with SVG diagrams, overriding versus extending, public/protected/private access modifiers, inheritance versus composition, pros and cons, the famous diamond problem, everyday examples from messaging apps to biological classification, an FAQ, and a six-line takeaway.

One instruction, delivered to different objects, produces different but each perfectly appropriate results. That is the entire secret behind polymorphism — one of programming’s most useful ideas. This thirteen-chapter guide unpacks what the word literally means (Greek for “many forms”), what polymorphism really is in code, why it matters, the two main types (compile-time overloading and runtime overriding) with real Python examples, the looser duck-typing philosophy, pros and cons, common pitfalls, and where you meet the pattern every day — from media players and payment systems to universal remote controls.

Encapsulation bundles data and the actions that work on it into one protected unit, then hides the messy inner details from everyone else. This twelve-chapter guide walks through what it really is, why every serious project relies on it, the four ingredients of a capsule, how it differs from abstraction and information hiding, the concrete techniques engineers use to achieve it, how the same idea scales from a single class up to microservices, plus a piggy-bank worked example, pros and cons, common pitfalls, and how encapsulation makes testing and change dramatically safer.

Long before software existed, people were designing complex things that had to stand up, work well, and feel right to humans — buildings. The rules they discovered along the way are the same ones a good software architect leans on today. This twelve-chapter guide walks through balance, emphasis, proportion, rhythm, unity and the datum, and simplicity — showing each principle first in physical buildings, then in software, with a side-by-side library-vs-bookstore example and the pitfalls to watch out for.

Architecture is the plan; infrastructure is what the plan gets built on. This friendly, twelve-chapter guide walks through both — what each one really means, how they stack together, the building blocks of infrastructure, on-prem vs cloud vs hybrid, Infrastructure-as-Code vs Architecture-as-Code, who owns what, and why mixing the two up costs teams real time and money.