You've seen it before. A function that starts with a modest if statement checking what kind of object it's dealing with, then choosing the right behavior. A month later, there are four branches. Six months in, someone adds a seventh else if clause and quietly hopes nothing breaks.

This is one of the most common design smells in object-oriented codebases. Scattered conditional logic that inspects an object's type to decide what to do with it is a signal that behavior lives in the wrong place. The object itself should already know how to behave. That's the entire promise of polymorphism.

Replacing type-checking conditionals with polymorphic dispatch isn't just an academic exercise in design purity. It's a practical strategy that reduces the number of places you need to change when requirements evolve, eliminates entire categories of bugs, and makes your code dramatically easier to extend. Let's examine exactly how and when to make this shift.

The pattern is deceptively simple. You receive an object, check its type or a type-discriminating field, and branch into different behavior accordingly. Maybe it's a switch on a string like "credit", "paypal", or "crypto". Maybe it's an instanceof check. Either way, the calling code is doing work that should belong to the objects themselves.

The real problem isn't a single conditional. It's that the same type check tends to replicate across the codebase. One function checks the payment type to calculate fees. Another checks it to format a receipt. A third checks it to determine refund eligibility. Each of these is a separate location where every new type requires a change. Miss one, and you have a bug that might not surface until production.

This violates the Open-Closed Principle at a fundamental level. Your system should be open for extension—adding a new payment type—without requiring modification to existing logic spread across dozens of files. When conditionals are the mechanism for variation, every extension is a modification. Every modification is a risk.

The smell has a clear diagnostic: if you search your codebase for the same set of type values appearing in multiple conditional blocks, you've found missing abstractions. Those branches represent behaviors that vary by type, which is precisely what polymorphism was designed to handle. The type itself should carry its behavior with it, not force external code to interrogate and decide.

Takeaway

If you find the same type check in more than one place, you're looking at behavior that doesn't have a home yet. Each duplicated conditional is an abstraction waiting to be born.

The fix is to give each variant its own object that encapsulates the differing behavior behind a common interface. This is the Strategy pattern at its core, though it also manifests as subtype polymorphism through inheritance hierarchies. The key idea is the same: replace the conditional with a method call on an object that already knows what to do.

Consider a notification system that checks whether to send an email, a push notification, or an SMS. Instead of a function with three branches, you define a NotificationChannel interface with a send method. Each channel—EmailChannel, PushChannel, SmsChannel—implements that interface. The calling code simply invokes channel.send(message) without knowing or caring which type it holds.

The transformation follows a repeatable process. First, identify the conditional branches and the behavior each one performs. Second, define an interface or abstract class that represents the common contract. Third, create a concrete implementation for each branch. Fourth, replace the conditional with a polymorphic method invocation. The calling code shrinks, often dramatically, because the decision logic has moved into the type system rather than sitting outside it.

This isn't about adding complexity. It's about relocating complexity to where it can be managed. Each implementation class is small, focused, and independently testable. Adding a new variant means adding a new class that conforms to the existing interface—no existing code changes, no risk of breaking what already works. The calling code that was once a fragile web of conditionals becomes a single, stable line.

Takeaway

Polymorphism doesn't remove decision-making from your system. It moves each decision into the object that has the most context to make it, so the rest of your code never needs to ask.

If polymorphism eliminates type checks from your business logic, you still need one place that knows which concrete type to create. That's the factory's job. A factory or registry examines the input—a configuration value, a user selection, an incoming payload—and returns the appropriate polymorphic instance. From that point forward, no other code needs to know the concrete type.

This creates a powerful architectural boundary. The factory is the single point of type knowledge in your system. When a new variant appears, you modify the factory and add a new implementation class. Nothing else changes. Compare this to the pre-refactoring state where a new type required hunting through every conditional that referenced the old set of types.

Registries take this further by making even the factory open for extension. Instead of a hardcoded mapping, strategies register themselves—often at startup—so the system discovers available implementations dynamically. Plugin architectures rely on exactly this mechanism. Your core application doesn't need to know about a payment provider that hasn't been written yet; it just needs to trust that whatever arrives will conform to the interface.

The combination of polymorphism and factory integration produces a clean separation of concerns. Creation logic lives in one place. Behavioral variation lives inside the objects. And client code operates entirely against abstractions. This is the architecture that scales gracefully: the cost of adding the tenth variant is the same as adding the second.

Takeaway

Concentrate type knowledge into a single creation point—a factory or registry—and let the rest of your system work with abstractions. The reward is that extending your system becomes an additive act, not a surgical one.

The instinct to write an if statement is not wrong—it's often the right first step. But when the same type-driven conditional appears in multiple places, it's time to recognize that your code is telling you something: there's an abstraction missing.

Extract the varying behavior into polymorphic objects, funnel creation through a factory, and let client code operate against interfaces. The result is a system where new requirements mean new classes, not new branches in old functions.

This is one of the most reliable refactoring patterns in software design. Master it, and you'll find that the code you write today stays welcoming to the developers—including future you—who need to change it tomorrow.