In software design, side effects are like hidden tripwires. They’re the unpredictable behaviors that occur when a method does more than its primary job, often relying on internal assumptions or changing external state. As I explained during a recent mentoring session, “Side effects are inherently unpredictable. When methods have clear inputs and outputs, you know what you’re getting. Side effects, on the other hand, make things messy.” This article explores why side effects matter, the problems they introduce, and how you can design methods to avoid them entirely.

What Are Side Effects?

A side effect occurs when a method modifies or interacts with something outside its immediate scope — like updating a global variable, writing to a file, or changing the state of a member variable. While this can seem harmless in small, contained systems, side effects introduce complexity and make debugging harder.

Take this example from a mentoring conversation: “When you call a method, you hope it’s writing the right list to the file. But if that method relies on some internal state, you’ve just created a hidden assumption that could break things later.” The problem isn’t just that side effects are harder to track; it’s that they reduce your code’s predictability and reusability.

Why Side Effects Are Problematic

  1. Reduced Testability

Side effects make it harder to write reliable unit tests. When a method modifies internal state or interacts with external systems, you can’t test it in isolation. As I explained: “If your method depends on internal assumptions instead of explicit inputs, you’re not testing the method — you’re testing the entire context.”

  1. Hidden Dependencies

Side effects create implicit dependencies between components, increasing the chance of bugs. For instance, in our discussion, I noted: “If a method assumes that a specific member variable will be updated beforehand, you’ve built a trap for the next developer — or even for yourself six months later.”

  1. Unpredictable Behavior

The more a method interacts with external systems or shared state, the harder it is to predict its behavior. This unpredictability makes debugging a nightmare. As I pointed out: “Side effects are fine in a very simple class, but as your system grows, they become liabilities.”

Best Practices to Avoid Side Effects

  1. Favor Explicit Inputs and Outputs

Design methods that take in everything they need and return a clear result. This eliminates reliance on hidden state. As I told my mentee: “When you pass a list as a parameter to a method, you’re not guessing what it’s working with — you know.”

  1. Encapsulate State Changes

If your method needs to modify state, encapsulate those changes in a single, well-defined location. For example, during the session, I suggested centralizing file writes to reduce surface area: “I’d prefer there to be one place where we’re writing to the file. That way, you always know where to look.”

  1. Isolate External Interactions

Interactions with external systems, like file I/O or database operations, should be isolated in methods dedicated to those tasks. This approach makes your code easier to mock and test.

  1. Avoid Implicit Assumptions

As I emphasized: “When methods have inputs and outputs, you can trust them to behave predictably. Side effects are unpredictable because they rely on things you can’t see or control directly.” Build methods with explicit preconditions instead of relying on implicit assumptions about the environment.

Designing for Clarity

Avoiding side effects isn’t just about writing better code — it’s about creating software that’s easier to maintain and understand. As I explained: “You need to compartmentalize the requirements of each component. Treat each piece of code as if it’s the only thing in the universe.” This mindset ensures every method is self-contained and focused on its specific role, without spreading dependencies across your system.

For example, in a class that synchronizes an in-memory list with a file, you might write a method that takes the list as an input and writes it to the file. This approach eliminates the need for implicit state, making the method reusable and predictable.

Iterative Improvement: The Power of Re-Evaluation

As I mentioned during the session: “Sometimes you make a design choice that seems right at the time, and later you realize it wasn’t the best option. That’s okay — design is iterative.” Start with simple changes, like parameterizing methods, and refine them over time as your system evolves. The goal is to create code that grows with your application, not against it.

In one case, my mentee and I discussed replacing direct calls to file.write with a single method. This change not only reduced redundancy but also improved testability by centralizing file operations. It’s a small but meaningful step toward eliminating side effects.

Conclusion

Side effects are the silent saboteurs of software design. They creep in through implicit assumptions, hidden dependencies, and scattered state changes, creating unpredictability and reducing testability. But by favoring explicit inputs and outputs, isolating state changes, and designing with clarity, you can eliminate these pitfalls.

As I often say: “In design, there’s no single ‘right’ answer. But there are better answers, and those are the ones that make your code predictable, maintainable, and robust.” By minimizing side effects, you’ll build systems that not only work today but remain reliable for years to come.