Codebase

Our codebase is easy to understand and work with.

What is codebase quality

In the context of developer experience, codebase quality refers to how easy it is for developers to understand and modify the organization's code. A high-quality codebase is well-structured, documented, and maintainable, enabling developers to efficiently navigate, comprehend, and extend the code with minimal friction.

Codebase quality encompasses several key attributes:

• Readability: How easily developers can read and understand the code
• Maintainability: How easily the code can be modified or extended
• Documentation: The availability and quality of supporting documentation
• Architecture: The overall structure and organization of the code
• Technical debt: The accumulation of suboptimal coding decisions that require future remediation

How codebase quality can improve developer experience and productivity

Accelerates onboarding and knowledge transfer

A clean, understandable codebase significantly reduces the time it takes for new team members to become productive.

Reduces cognitive load and context switching

When codebases are well-organized and intuitive, developers can focus on solving problems rather than deciphering what existing code does. This reduces mental fatigue and improves focus.

Enables faster iteration and innovation

Teams can implement new features and fix bugs more quickly when the codebase is easy to modify. This directly impacts business outcomes through faster time-to-market and improved customer satisfaction.

Reduces errors and defects rates

A well-structured codebase makes it easier to identify potential issues before they reach production, resulting in fewer bugs and more reliable software.

Why codebase quality is important

Codebase quality is crucial for successful development teams because it directly impacts their ability to deliver value consistently and sustainably. Poor codebase quality leads to several critical issues:

Increased development time: When code is difficult to understand, even simple changes can take significantly longer to implement.

Higher defect rates: Complex, hard-to-understand code leads to more bugs and regressions.

Developer frustration and burnout: Constantly wrestling with a difficult codebase leads to frustration and can contribute to developer burnout and turnover.

"A significant part of our lengthy meetings revolves around figuring out things we should already know. We lack knowledge about the product we've been building for the past decade. When we need to modify something built five years ago, we have no idea how to do it. We waste hundreds of hours monthly just trying to locate someone knowledgeable or documentation that could guide us."

Delivery Manager at Online Gaming Platform

Institutional knowledge bottlenecks: When code is hard to understand, knowledge tends to become siloed with a few experienced developers, creating dangerous dependencies.

Resistance to change: Teams become reluctant to make necessary changes for fear of breaking existing functionality, leading to technical stagnation.

Higher operational costs: More time spent on maintenance means less time available for innovation and new features.

How to measure codebase quality

"The codebase is easy to understand and modify."

This survey question directly assesses how developers perceive the understandability and modifiability of the codebase they work with daily. By measuring this sentiment across teams and tracking it over time, organizations can:

1. Identify areas of the codebase that may need refactoring or improved documentation
2. Track the impact of codebase improvement initiatives
3. Compare codebase health across different teams or projects
4. Correlate codebase quality with other performance metrics like deployment frequency or change failure rate

Additional metrics that complement this survey question include:

• Cycle time: How long it takes to implement, test, and deploy changes
• Change failure rate: The percentage of changes that result in defects or rollbacks
• Code churn: The frequency with which code is rewritten or significantly modified
• Static analysis metrics: Automated measures of code complexity, duplication, and test coverage

Why codebase quality works

Investing in codebase quality provides compounding returns over time. While it may require initial investment to refactor problematic code or improve documentation, these efforts pay dividends through:

Sustained developer productivity: Teams can maintain consistent velocity without slowing down as the codebase grows.

Knowledge democratization: More developers can effectively contribute across different areas of the code.

"We strive for a welcoming culture that encourages everyone to participate. I've been reflecting on what created this culture and how it differs from other places I've worked. First, there are no silos in the frontend—people aren't territorial about their code. Instead of 'this is my code, don't touch it,' we embrace large projects that affect the entire codebase. We're comfortable with this approach, actively want people to contribute across the codebase, and encourage them to do so."

Director of Engineering at Cloud Observability Platform

Reduced technical debt accumulation: Clean code begets more clean code, as developers are more likely to maintain standards when working with well-structured code.

Improved architectural decisions: A clear codebase makes it easier to reason about and implement architectural improvements.

Enhanced team morale: Developers take pride in working with clean, high-quality code.

How to improve codebase quality

Establish clear coding standards and practices

Define and document coding standards, architectural principles, and best practices. Ensure these are easily accessible and regularly updated.

"Over the years, I've observed that standards are essential for any developer experience initiative. We all know companies go through growth phases - sometimes very rapid growth - where the focus shifts to just shipping things quickly. During these periods, there's often a mindset that standards or consistent language choices aren't important. I'm not suggesting we need perfect uniformity in everything we do, but we should establish some basic standards for consistency."

Director of Engineering at Software Development Company

Prioritize code reviews and knowledge sharing

Implement thorough code review processes that focus not just on correctness but also on maintainability, readability, and adherence to coding standards.

"And then what we did is we launched kind of a workshop series where like, we went or like, you know, send people from the team to do multiple workshop across the company, you know, team by team to, like, have one, like smaller meetings or like, folks can ask questions. ... And we also launched guidelines about code organization and the architecture of the app and like how we were seeing this evolve and like trying to like balance out, you know, kind of moving fast for like CI gains but also like, yeah, kind of refocusing a bit on like code quality."

Director of Engineering at Cloud Observability Platform

Invest in refactoring and technical debt reduction

Allocate dedicated time for refactoring and technical debt reduction. This could be through regular "cleanup sprints" or by incorporating refactoring into everyday development work.

"I realized I had both high and low velocity committers. When I paired these different types of developers together on PRs and other work, I found I could unlock a lot more productivity between them. People started pushing code more frequently, and many gained the confidence to commit their changes regularly rather than holding onto them for the entire sprint or week before finally pushing at the end."

Sr Manager at Entertainment and Media Conglomerate

Improve documentation and knowledge management

Ensure code is well-documented and that architectural decisions are captured and accessible. Consider implementing developer portals or knowledge bases.

"The key improvement is in accessing documentation and how easily it can be connected and integrated now. Previously, teams were doing things their own way - some documentation here, some there, scattered all over. Now it's much easier to find and use. Plus, we've introduced standardization. So we're moving toward a system where it's easier for everyone to access and benefit from the documentation."

Dev Exp manager at Technology Company

Adopt modular architecture

Move toward more modular architectures (e.g., microservices or well-defined modules) where appropriate, to reduce complexity and coupling.

"These would be aspects like how easy it is to write tests, how easy it is to search for code references and in what ways. What else? How we can modularize certain parts of the codebase to build abstractions that allow us to develop more quickly."

Head of Engineering at Software Development Company

Implement automated code quality tools

Use static analysis tools, linters, and automated testing to continuously monitor and improve code quality.

"We also do code health and reviews, something like what Sonarqube does. So we also take access to the code base and start highlighting the issues there."

Co-Founder at Software Development Company

Foster a quality-focused culture

Build a culture where code quality is valued and where developers feel empowered to advocate for improvements.

"We can often feel and sense quality differences when working in different parts of the codebase. It's about how you visualize your modules and architecture to identify areas of varying quality. This visualization helps correlate where problems typically emerge, allowing us to target improvements in measurable source code quality or address design deficiencies in those specific areas."

Director of Engineering at Software Development Company

Benefits of codebase quality

For developers:

• Reduced frustration and cognitive load
• Faster onboarding and knowledge acquisition
• Greater confidence in making changes
• More time spent on interesting problems rather than debugging
• Improved work satisfaction and reduced burnout

For engineering managers:

• More predictable delivery timelines
• Easier resource allocation and team scaling
• Reduced risk from knowledge silos
• Lower onboarding costs for new team members
• Better visibility into system capabilities and limitations

For organizations:

• Faster time-to-market for new features
• Lower maintenance costs
• Improved product quality and customer satisfaction
• Better adaptability to changing business requirements
• Reduced risk from developer turnover

How do we balance velocity with code quality?

This is a common challenge. The key is recognizing that code quality is not at odds with velocity—in fact, it enables sustainable velocity over time. Some approaches include:

1. Invest in automated testing: This allows teams to move quickly while maintaining confidence in their changes.
2. Implement progressive refactoring: Improve code quality incrementally alongside feature development.
3. Set clear quality standards: Establish which quality aspects are non-negotiable versus areas where pragmatic tradeoffs can be made.
4. Measure both short and long-term metrics: Track not just immediate velocity but also maintenance costs over time.

"And then what we did is we launched kind of a workshop series where like, we went or like, you know, send people from the team to do multiple workshop across the company, you know, team by team to, like, have one, like smaller meetings or like, folks can ask questions. ... And we also launched guidelines about code organization and the architecture of the app and like how we were seeing this evolve and like trying to like balance out, you know, kind of moving fast for like CI gains but also like, yeah, kind of refocusing a bit on like code quality."

Director of Engineering at Cloud Observability Platform

How do we tackle a legacy codebase with significant quality issues?

Improving a problematic legacy codebase requires a strategic approach:

1. Visualize and measure: Map out the codebase to identify hotspots and measure quality metrics as a baseline.
2. Strangler pattern: Gradually replace problematic components rather than attempting a complete rewrite.
3. Improve incrementally: Focus refactoring efforts on areas that receive frequent changes.
4. Build a knowledge base: Document discoveries about the codebase as you go.
5. Set realistic expectations: Recognize that improvement will take time and communicate this to stakeholders.

How do we measure the ROI of codebase improvement initiatives?

Measuring return on investment for codebase quality requires looking at both leading and lagging indicators:

1. Leading indicators: Developer satisfaction, time spent on maintenance versus new features, code review cycle time
2. Lagging indicators: Defect rates, time-to-market for new features, onboarding time for new developers

These metrics can be combined with business metrics like customer satisfaction and revenue growth to demonstrate how codebase quality enables business outcomes.

How do we get buy-in from business stakeholders for codebase improvement work?

Securing support for codebase quality initiatives often requires translating technical concerns into business outcomes:

1. Quantify the current impact: Show how much time is spent dealing with codebase issues versus delivering value.
2. Demonstrate opportunity cost: Illustrate features or innovations that could be delivered if less time was spent on maintenance.
3. Use risk management framing: Position codebase quality as risk mitigation for business continuity.
4. Start small and show results: Begin with focused improvements that deliver measurable benefits quickly.

"Because as the systems are so broken, we're constantly firefighting, we're constantly being reactive. And then because we're doing reactive work, it means we don't have bandwidth to actually enhance those systems to trigger less of that reactionary work."

Sr. Software Engineering Manager at Software Development Company

What tools and frameworks can help improve codebase quality?

Several types of tools can support codebase quality improvement:

1. Static analysis tools: SonarQube, ESLint, StyleCop, etc. for automated code quality checks
2. Architecture visualization: Tools or custom visualization scripts
3. Documentation generators: JavaDoc, JSDoc, Sphinx, etc. for API documentation
4. Developer portals: Tools like Backstage (Spotify) to centralize code and knowledge management
5. Refactoring assistants: IDE features and AI-powered tools that help with code restructuring

"Internal developer portals like Backstage have become increasingly important because most companies don't even know how many tools they have. They lack a catalog of their tools and applications, including where they're deployed. Organizations are struggling to create a centralized place where they have visibility into everything happening across the enterprise. This lack of visibility creates a significant barrier to effective communication and collaboration."

Global Head of DevOps at Software Development Company

How do architectural decisions impact codebase quality?

Architecture significantly influences how easy a codebase is to understand and modify:

1. Modularity: Well-defined boundaries between components reduce cognitive load and allow for easier changes.
2. Consistent patterns: Using consistent architectural patterns makes the codebase more predictable and easier to navigate.
3. Appropriate abstractions: The right level of abstraction makes code more maintainable without adding unnecessary complexity.
4. Evolution strategy: Having a clear path for how the architecture evolves prevents ad-hoc decisions that degrade quality over time.

"We identified areas in the organization with strongly shared codebases. Some parts of the organization are still transitioning away from a monolith structure, so they have split functionalities but within the same codebase. This creates significant conflict and friction in their operations, unlike other teams that work with completely independent codebases."

CTO at IT Services Company