Why Over-Emphasising DRY Can Hurt Code Quality

The “Don’t Repeat Yourself” (DRY) principle is a foundational tenet of software development, widely taught as a means to create more maintainable, modular, and efficient code. But despite its acclaim, DRY has a less-discussed downside, particularly when developers wield it indiscriminately. Overzealous application of DRY can introduce unnecessary abstractions, reduce readability, and ultimately create more technical debt rather than reducing it. This article will explore why DRY is sometimes dangerous, examining both practical and theoretical issues, and outline strategies for applying it in a balanced, effective manner.

1. Understanding DRY's Original Purpose

At its core, DRY was introduced to prevent "knowledge duplication," not necessarily line-for-line code duplication. It encourages developers to avoid re-implementing logic or business rules in multiple places, which would increase the cost of changes by requiring updates in multiple locations. The idea was that duplicating "knowledge" could lead to inconsistencies, where one part of the code changes but others don’t, resulting in errors.

However, DRY has evolved into a more rigid mandate in many teams, focusing on eliminating even minor similarities in code. This perspective misses the underlying purpose of DRY and leads to more rigid, brittle code structures. Instead of creating an adaptable codebase, misapplied DRY can lead to code that’s difficult to understand, maintain, and extend.

2. The Dangers of Premature Abstraction

One of the primary issues with overusing DRY is premature abstraction. Developers often create abstractions to encapsulate what they perceive as similar behaviour, but when this is done prematurely, it forces a narrow view on the code's structure before the problem is fully understood.

For example, imagine a developer is working on a module that processes different food items. Cooking an egg and cooking meat might both involve "placing an ingredient on a hot surface," but these processes differ significantly. Eggs might require a quick sear, while meat might need gradual cooking over a longer period. Prematurely abstracting this "cooking" process may initially save a few lines of code, but it also removes the flexibility to handle these processes independently in the future.

By focusing on DRY too early, developers may close doors to better abstractions, losing the opportunity to improve the design once they have a clearer understanding of the domain. This often results in "de-DRYing" later or shoehorning new requirements into an existing, ill-fitting abstraction.

Practical Consequences of Premature Abstraction:

• Reduced Readability: When every function or method is reduced to share an abstraction, it can be challenging for others (or even the original developer) to understand the code's intent at a glance.
• Increased Complexity: Developers often need to add configuration options or conditional logic to make a single abstraction work for all cases, making the code harder to follow and maintain.
• Fragile Code: Abstractions that try to do too much become brittle, as minor changes in one part of the code can cause unintended effects elsewhere.

3. Losing Sight of the Data Structure

Overuse of DRY can also obscure the structure and flow of data in an application, particularly when developers attempt to fit diverse data manipulations into a common base structure. This often happens when they create a generic “wrapper” class or base structure to represent different entities that share only superficial similarities. While this can save lines of code in the short term, it sacrifices clarity in data handling, which is crucial for understanding and debugging.

In applications with complex data flows, preserving the "shape" of the data is essential. Distinct operations and data structures offer clear, logical boundaries that help convey the data's purpose and relationships. When developers "DRY up" structures, they may hide these boundaries, making it difficult to grasp the original data intent. This can also introduce unintended behaviours, as methods become responsible for handling diverse data forms they weren’t designed to manage.

4. The Myth of DRY and Maintainability

One of the most commonly cited reasons for enforcing DRY is maintainability. The argument is that having a single source of truth for a piece of logic will make it easier to update that logic in the future. However, in practice, the supposed benefits of DRY often don’t outweigh the drawbacks, especially for code that rarely changes.

For instance, developers might fear the need to modify similar code in multiple locations, but modern development tools such as find-replace or ripgrep make it easy to search and update patterns across a codebase. In reality, DRY should be applied with consideration for how often the code is likely to change. If the code in question is stable and unlikely to undergo frequent updates, the cost of maintaining minor duplication is likely far lower than the complexity introduced by trying to create a single abstraction.

Moreover, studies have shown that duplication is often less problematic than poorly conceived abstractions. Abstractions that are forced can lead to confusing dependencies, making the code harder to test, debug, and modify. As software engineer Sandi Metz famously said, “Duplication is far cheaper than the wrong abstraction.” DRY should be seen as a means to an end, not an end in itself.

5. DRYing with a Pinch of Salt: Practical Tips

Applying DRY effectively goes beyond simply removing duplication. It requires balancing readability, maintainability, and adaptability. Below are practical strategies:

• Wait Until the Abstraction Emerges Naturally: Avoid rushing into abstractions. Allow similar code patterns to develop until a clearer, more robust abstraction becomes evident. This prevents the creation of rigid structures that can hinder adaptability.

• Apply the AHA (Avoid Hasty Abstractions) Principle Alongside DRY: AHA encourages developers to avoid premature abstractions. By letting abstractions grow naturally from clear patterns, we prevent forced generalisations that could lead to maintenance difficulties down the line.

• Embrace OCF (Optimise for Change First): OCF encourages designing code with adaptability in mind, making it easier to modify as requirements evolve. Before abstracting code to reduce duplication, assess whether each section is likely to change independently. OCF helps prioritise flexible, modular code over rigid DRY abstractions.

• Follow the Single Responsibility Principle (SRP): SRP states that a function or module should have one and only one reason to change. When applying DRY, SRP helps ensure that abstractions are clean and cohesive, rather than attempting to handle multiple unrelated tasks. By adhering to SRP, we avoid “kitchen-sink” abstractions that can become unwieldy and confusing as they try to serve too many purposes.

• Use the Small Functions Principle: Small, focused functions make code easier to understand, test, and modify. Instead of creating a large, shared abstraction to eliminate duplication, consider breaking code into smaller, single-purpose functions that communicate intent clearly. Small functions encourage simplicity and modularity, both of which help preserve the flexibility needed for future changes.

• Focus on Constants and Closed Abstractions: Constants, configurations, and values that are stable are good candidates for DRY. JSON values, enums, and other fixed elements can safely be centralised without risking rigid abstractions that need frequent modification.

• Use DRY for Knowledge, Not Syntax: DRY is about eliminating duplicated knowledge, not just identical lines of code. Focus on sharing logic, calculations, and rules that have a real benefit when centralised.

• Assess the Frequency of Change: Before creating an abstraction, consider if the code is likely to evolve independently. If similar sections will diverge over time, keeping them separate may ultimately be more maintainable.

6. Recognising and Avoiding Zealotry in Code Reviews

One unfortunate side effect of DRY’s popularity is the zealotry that can develop around it. Many developers, especially in code reviews, become so focused on enforcing DRY that they fail to see the bigger picture, such as the code’s readability, maintainability, and adaptability. This DRY zealotry often manifests as nitpicking in code reviews, where reviewers insist on combining even loosely related pieces of code.

To mitigate this, development teams should encourage a balanced view of DRY. Code reviews should focus on the intent of the code rather than enforcing superficial principles like DRY at all costs. Here are some guidelines to foster a more balanced code review culture:

• Encourage Developers to Defend Their Design Choices: Developers should be able to justify their choices when they diverge from DRY. This encourages thoughtful discussion about trade-offs and design decisions.
• Focus on Readability and Domain Logic: Instead of forcing every line to adhere to DRY, consider whether the code clearly expresses the domain's logic and intent. If enforcing DRY makes it harder to understand the business rules or purpose of a section, it’s likely a poor abstraction.
• Use DRY as a Discussion Point, Not a Mandate: In code reviews, DRY should be treated as a point of consideration rather than a rule. A good code review culture is one that prioritizes meaningful abstractions, flexibility, and simplicity over rigid adherence to principles.

7. The DRY Trap in Specific Communities

The issue of over-DRYing isn’t equally prevalent across all development communities. Some programming communities or frameworks encourage excessive adherence to DRY, creating cultures where minor duplication is considered an unforgivable offense. Developers working in these environments should be cautious about adopting DRY as an automatic reflex and instead strive for a pragmatic approach to duplication.

A balanced DRY approach involves understanding when to embrace some duplication, particularly when working with frameworks that heavily promote DRY practices. It’s essential to assess whether DRY truly improves the code or if it merely reflects the coding norms of the framework.

8. The Benefits of Strategic Duplication

In some cases, duplication is not just acceptable but desirable. Here’s why intentional duplication can sometimes be the best choice:

• Clearer Intent: When similar operations are duplicated, each occurrence can retain its unique purpose, making the intent clearer and reducing the mental overhead of understanding an abstraction.
• Independent Evolution: Duplication allows for similar pieces of code to evolve independently without impacting each other. This can be crucial when requirements change for only one instance of the duplicated code.
• Reduced Complexity: A simple, duplicated solution can often be more straightforward than a complex, overly generalised one, especially for code that isn’t expected to change frequently.

DRY is a powerful concept, but like any tool, it must be used judiciously. Overzealous application of DRY can lead to brittle code, premature abstractions, and decreased readability. By taking a thoughtful approach—considering factors such as readability, flexibility, and the frequency of change—developers can avoid the pitfalls of DRY and create more resilient, maintainable code. Remember, duplication is often cheaper than a poor abstraction. DRY should be a guide, not a strict rule, and balancing it with a clear understanding of the domain and future requirements is key to sustainable software development.