Documentation as code: Principles, workflow, and challenges

What is documentation as code?

Documentation as code (DaC) is a development philosophy that treats software documentation with the same respect and attention as software code. Just like code, documentation is written in plain text, stored in version control systems, and subject to the same rigorous review and testing processes.

DaC leverages the same tools and workflows that developers use for writing and maintaining software code. The goal is to improve the quality, accuracy, and usability of documentation by adopting the principles of modern software development. In essence, it’s about bringing the power of version control, automated testing, and continuous integration to the realm of software documentation.

This is part of a series of articles about code documentation.

Core principles of documentation-as-code tools 

Treating documentation with the same rigor as code

Documentation as code places documentation at the same level of importance as the code itself. This means that documentation should be written, reviewed, updated, and maintained with the same intensity and commitment as the software code. Just like code, documentation errors can lead to misinformation, confusion, and ultimately, lower product quality.

Storing documentation in version control

One of the key principles of documentation as code is the storage of documentation in version control systems, just like code. This allows for tracking changes over time, easy collaboration among team members, and the ability to revert to previous versions of the documentation if needed. Storing documentation in version control also ensures that the documentation always reflects the current state of the project.

Automation of documentation generation and deployment

Automation is a cornerstone of modern software development, and documentation should be no exception. By automating the process of documentation generation and deployment, teams can ensure that the documentation is always up-to-date and available for users. This not only reduces the manual effort required to maintain the documentation, but also ensures that users always have access to the latest information.

Peer review processes for documentation updates

Just like code, updates to the documentation should be subject to peer review. This ensures that the documentation is accurate, consistent, and easy to understand. It also helps to catch errors and inconsistencies before they make their way into the final product.

Learn more in our detailed guide to code documentation tools.

Benefits of documentation as code 

Here are the key benefits of DaC for development organizations:

Improved consistency and accuracy

By treating documentation with the same rigor as code, teams can ensure that their documentation is consistent and accurate. This means that users can trust the documentation to provide reliable and up-to-date information about the software.

Collaboration and iterative improvement

DaC promotes collaboration among team members. By storing documentation in version control systems, teams can easily collaborate on the creation and maintenance of documentation. This fosters an environment of iterative improvement, where the documentation is continuously updated and refined based on feedback and changes in the software.

Flexibility in documentation formats and platforms

One of the key benefits of DaC is its flexibility in terms of documentation formats and platforms. Because the documentation is written in plain text, it can easily be converted into various formats such as HTML, PDF, or Markdown. This also allows for easy integration with various documentation platforms.

Integration with CI/CD pipelines

DaC fits seamlessly into modern CI/CD pipelines. With automation in place, documentation can be generated and deployed automatically as part of the software release process. This ensures that the documentation is always in sync with the latest version of the software.

Learn more about AI for software development in our guide for AI coding tools.

Process and workflow of DaC 

Here are the main stages of the DaC workflow:

Plain text authoring

DaC starts with transitioning documentation to a simple, plain text format. This way, you can use any text editor to create or modify the documentation. Plain text is universal and doesn’t require any specific software to read or write, making it accessible to everyone.

Plain text files can be easily version controlled, diffed, and merged. They’re also platform independent and can be opened on any operating system without worrying about compatibility issues.

Using markup languages like Markdown or reStructuredText is beneficial. These languages allow you to format your text, making it more readable and organized. They also support conversion to other formats like HTML or PDF, allowing you to publish your documentation in various formats.

Source control

The use of source control systems like Git for documentation provides numerous benefits including versioning, collaboration, and traceability.

Version control allows you to track changes, maintain multiple versions, and even revert changes if necessary. This is particularly useful when you are working with a team of developers, as it allows everyone to work on the documentation simultaneously without any conflicts.

Moreover, traceability is another critical benefit that source control provides. With it, you can link your documentation to your code, making it easier to understand the relationship and dependencies between them.

Publishing

Once your documentation is written and versioned, it needs to be published so that it can be accessed by your users. This can be done through various channels like a dedicated documentation website, GitHub wiki, or even directly from your source code repository.

Publishing your documentation is not just about making it accessible, but also about making it easy to navigate and search. A well-structured documentation site allows your users to find the information they need quickly and easily. It also provides a platform for feedback, enabling you to continuously improve your documentation based on your users’ needs and experiences.

Automation

The final stage in the workflow of documentation as code is automation. Automation involves using tools to automatically generate, update, and publish your documentation. This not only saves you time and effort but also ensures consistency and accuracy.

Automation can be achieved through various tools and frameworks like Jekyll, Sphinx, or MkDocs. These tools integrate with your source control and can automatically generate your documentation every time you commit changes to your repository.

Read more in our detailed guide to AI Code Documentation.

Best practices in documentation as code 

Here are a few best practices that can help you make the most of DaC workflows.

Maintaining documentation modularity

Modularity involves breaking down your documentation into smaller, self-contained units. This makes it easier to write, maintain, and navigate your documentation.

Modularity also aids in collaboration. Different team members can work on different modules without stepping on each other’s toes. It also makes it easier to track changes and understand the impact of a change in one module on the rest of the documentation.

Continuous integration of documentation

Continuous integration (CI) of documentation involves integrating your documentation with your CI pipeline, ensuring that it is always up-to-date with your code.

CI of documentation helps prevent outdated or inaccurate documentation. It ensures that your documentation is always in sync with your code, providing your users with the most accurate and current information.

Frequent updates and reviews

Just like code, documentation needs to be continually updated and reviewed to ensure accuracy and relevance. Regularly updating your documentation ensures that it reflects the current state of your code. Regular reviews, on the other hand, help catch errors, inconsistencies, and areas of improvement.

Challenges of traditional code documentation 

While DaC practices can be very beneficial, the documentation as code pattern does not solve the major problem of code documentation — it takes time. Even if documentation is stored in plain text files and efficiently managed, someone still needs to write it. Let’s review some of the key challenges of code documentation, which are not alleviated by DaC workflows.

Code documentation uses valuable development resources

The first challenge that many developers encounter with traditional code documentation is the significant amount of time and resources it consumes. In most cases, code documentation is a manual process that requires developers to pause their coding activities and dedicate substantial time to write, structure, and review their code documentation.

This process is not only time-consuming but also diverts attention away from the core development activities. It’s like asking a chef to stop cooking and start documenting each ingredient, cooking step, and the rationale behind their culinary choices. This would waste time chefs could use on their creative work.

Code documentation must be frequently updated

As the codebase evolves, changes must be reflected in the documentation. However, with the rapid pace of software development, keeping documentation up-to-date can be a daunting task.

As development teams implement new features, fix bugs, and refactor code, the associated documentation must be updated accordingly. This constant need for updates can quickly turn into a documentation nightmare, either wasting resources or leading to outdated or incorrect information that can mislead stakeholders.

Code documentation is rarely comprehensive

Finally, traditional code documentation is often incomplete or lacks depth. This issue arises because, in the rush of agile development pipelines, documentation is often deprioritized or hastily written. As a result, crucial details might be omitted, and entire components might lack documentation, leading to a lack of clarity and understanding for anyone trying to comprehend the codebase.

Moreover, not all developers are good at or enjoy writing extensive documentation. Sometimes, developers might write a brief, cryptic explanation that makes sense to them but may be difficult for others to understand. Consequently, the code documentation fails to serve its purpose of enhancing code readability and maintainability.

Automating code documentation with Tabnine

Given the challenges of traditional code documentation, recent advances in generative AI can be a big help to development teams. Tabnine is the AI code assistant that helps development teams of every size use AI to accelerate and simplify the software development process without sacrificing privacy, security, or compliance. Tabnine boosts engineering velocity, code quality, and developer happiness by automating the coding workflow through AI tools customized to your team. Tabnine supports more than one million developers across companies in every industry. 

Unlike generic coding assistants, Tabnine is the AI that you control:

It’s private. You choose where and how to deploy Tabnine (SaaS, VPC, or on-premises) to maximize control over your intellectual property. Rest easy knowing that Tabnine never stores or shares your company’s code.  

It’s personalized. Tabnine delivers an optimized experience for each development team. It’s context-aware and delivers precise and personalized recommendations for code generation, code explanations, and guidance, and for test and documentation generation.

It’s protected. Tabnine is built with enterprise-grade security and compliance at its core. It’s trained exclusively on open source code with permissive licenses, ensuring that our customers are never exposed to legal liability.

The Tabnine in IDE Chat allows developers to communicate with a chat agent in natural language and get assistance with various coding tasks, such as:

• Generate new code 
• Generating unit tests 
• Getting the most relevant answer to your code
• Mention and reference code from your workspace
• Explain code
• Extending code with new functionality
• Refactoring code
• Documenting code

Read more about AI for software development in our guide for AI coding tools.

Onboarding Agent for Tabnine Chat
Tabnine Onboarding Agent helps developers onramp to a new project faster. For developers who are new to an organization or existing developers who are new to a project, the Onboarding Agent provides a comprehensive overview of key project elements, including runnable scripts, dependencies, and overall structure to help them get up to speed effortlessly.

Here are a few examples showing how Tabnine can be used to generate code documentation:

Large development teams can’t function effectively unless everyone commits to writing thorough documentation, the thing is most developers would rather be writing code than documenting it. Tabnine makes generating documentation easy. Simply highlight the code you want to document, and then ask Tabnine through your chat window to create documentation. With local and global context awareness enabled Tabnine will generate documentation that’s in alignment with your coding standards and formatting.

Try Tabnine for free today or contact us to learn how we can help accelerate your software development.