Technical debts are collective shortcuts and compromises made during a software development process. While such shortcuts may seem like a quick escape, they can affect a project's quality and reliability in the long term.
Unchecked technical debt may lead to a ballooning codebase with bugs, security vulnerabilities, and maintenance nightmares. Thus, any reliable software development company must manage technical debts to prevent development slowdown.
This blog thoroughly analyzes tech debt, its audit, and prevention. So keep on reading!
Types of technical debt
Technical debt manifests in various forms, hindering a project's long-term health. Here, we explore five common categories:
Code debt
This results from overly complicated, duplicate, or badly written code. Code debt is caused by inefficient algorithms, missing comments, and improperly written code. It makes the codebase harder to understand, modify, and test. Thus, this debt ultimately slows down development and raises maintenance costs.
Design debt
Design debt in a software development company results from a poorly planned system architecture. This architecture could be rigid, challenging to grow, or prone to single points of failure. Because of this debt, it is difficult to maintain the system's performance, add new features, and fix bugs. Additionally, interacting with other components may result in integration problems.
Documentation debt
A knowledge gap arises for developers when there is a lack of clear and current documentation. This includes poorly written instructions or outdated information. Debt from incomplete documentation causes developers to spend more time figuring out the codebase, reducing productivity and raising the possibility of mistakes.
Test debt
Test debt results from inadequate or poorly written assessments. As a result, the system may be vulnerable to bugs and regressions in areas of the codebase that have not been tested. Guaranteeing that new features don't have unforeseen aftermaths is challenging due to the lack of tests conducted on them.
Infrastructure debt
Technical debt arises from reliance on antiquated or improperly configured infrastructure. Some examples are outdated software versions, ineffective configurations, or insufficient monitoring tools. Infrastructure debt can result in performance problems, security flaws, and trouble scaling the system to accommodate expanding demand.
Impacts of technical debt on a software development company
Check out how technical debt can affect software developer companies:
Development speed and efficiency stall
Poorly written and complex code slows down development. Debugging and modifications become laborious tasks that impede the development cycle as a whole. Developers need to spend more time understanding such code's logic before making any changes. This low maintainability of complex code reduces productivity.
Software quality plummets
Technical debt leads to the development of defects and weaknesses in security. Taking quick fixes in the coding process can result in unexpected problems that emerge over time. Code that lacks unity and is closely coupled raises the chance of mistakes spreading throughout the system. Moreover, unresolved technical debt can result in security loopholes that make the system vulnerable to possible attacks.
Maintenance costs skyrocket
Addressing technical debt requires a substantial financial and labor-heavy effort. The more time passes without tackling it, the more convoluted and interrelated the issues become. This demands a considerable commitment of time and energy to rewrite code, enhance its structure, and develop thorough tests.
Increasing frustration among developers
Working with complicated, poorly documented code can be discouraging and frustrating for developers. If developers constantly struggle to comprehend and make changes to complex codebases, they may become less satisfied with their jobs and suffer from low morale. This can, therefore, adversely affect team output and impede creativity.
What to include in technical debt audit?
Here's how a custom software development company can audit technical debt:
Code analysis
Code smells: These are patterns in the code that indicate potential problems like code duplication, inefficiencies, or readability issues. Static analysis tools can identify these smells, allowing developers to investigate and refactor the code accordingly.
Duplication: Redundant code snippets inflate the codebase size and make maintenance cumbersome. Static analysis tools can effectively detect code duplication, prompting developers to consolidate or refactor the code for better maintainability.
Potential bugs: While not foolproof, static analysis tools can identify coding patterns that often lead to runtime errors. Early detection of such issues can save significant time and effort during the development process.
Code review
Readability issues: Complex code structures, lack of comments, and non-intuitive variable names can all hinder understanding. Code reviews ensure the code adheres to coding standards and best practices, promoting readability and maintainability.
Maintainability concerns: Code reviews can uncover areas where modifications or bug fixes might be overly complex or time-consuming. This early identification allows developers to refactor the code for better maintainability, reducing future development and maintenance costs.
Scalability bottlenecks: Code reviews can expose potential issues that might hinder the system's ability to scale as the user base or data volume grows. Addressing these issues proactively ensures the system can accommodate future growth.
Architecture review
Maintainability: A well-designed architecture promotes modularity, separation of concerns, and loose coupling between components. The review assesses how easily the architecture allows for modifications, bug fixes, and new feature integrations.
Scalability: The audit evaluates whether the architecture can handle increased user loads or data volumes without significant performance degradation. Identifying potential bottlenecks in the architecture allows a software development company to develop proactive scaling strategies. This ensures smooth operation as the system grows.
Single points of failure: The architecture review examines potential points in the system where a single component failure can bring the entire system down. Identifying and mitigating these points of failure improves overall system resilience.
Testing review
Test coverage: The audit determines the percentage of code covered by automated tests. Higher test coverage indicates better protection against regressions and hidden bugs.
Test quality: The review assesses the quality of existing tests. Well-written tests should be focused, specific, and provide clear information about the expected behavior. Poorly written tests can lead to false positives or negatives, hindering the debugging process.
Test automation level: The audit evaluates the extent to which testing is automated. A high level of automation allows for faster and more consistent testing, reducing manual effort and improving development velocity.
Documentation review
Completeness: The audit assesses whether all aspects of the codebase, including functionalities, configurations, and design decisions, are documented. Incomplete documentation leaves knowledge gaps, hindering understanding and increasing the risk of errors.
Accuracy: The review verifies the accuracy and currency of the documentation. Outdated documentation can mislead developers and waste time deciphering the codebase.
Clarity and conciseness: The audit evaluates whether the documentation is comprehensible, concise, and easy to understand. Complex or poorly written documentation can be just as detrimental as a lack of documentation.
Preventing and managing technical debt in a software development company
Following are some strategies by which a software development consulting company can reduce tech debt:
Coding standards and best practices
Improved code readability: Consistent formatting and naming conventions enhance the readability of code, making it more accessible for all developers. This shortens the time required for new team members to get up to speed and simplifies future updates.
Reduced errors: Adhering to best practices, such as proper error handling and input validation, is crucial. Thus, coders can avoid common coding mistakes that lead to bugs and security vulnerabilities.
Maintainability: Code written following established standards is easier to modify and extend, promoting long-term maintainability of the codebase.
Continuous integration and testing
Early detection of issues: Continuous integration (CI) and continuous testing (CT) serve as protective measures, identifying possible problems at an early stage. Thus, bugs and regressions are identified swiftly, allowing for faster resolution before they grow in propertion.
Improved code quality: CI entails regularly merging code updates from various developers into a central repository. CT involves automated testing of the codebase after each integration. Additionally, frequent testing incentivizes developers to write cleaner, more maintainable code from the outset.
Reduced risk: CI/CT helps mitigate the risk of introducing defects into production environments by catching issues early.
Refactoring
Reduce code complexity: Code can become convoluted over time in a software development company. Refactoring simplifies complex logic, making the code easier to understand and maintain.
Eliminate code duplication: Redundant code snippets inflate the codebase and hinder maintainability. Refactoring can identify and consolidate duplicated code, streamlining the codebase.
Improve code maintainability: By refactoring code into well-structured, modular components, developers can modify and extend the codebase more efficiently in the future.
Documentation
Reduce knowledge gaps: Comprehensive documentation acts as a knowledge repository, providing new developers a clear understanding of the system's functionalities, design decisions, and configurations.
Minimize errors: Well-documented code reduces the risk of developers making assumptions or introducing errors due to a lack of understanding.
Improve efficiency: Clear documentation allows developers to navigate the codebase more efficiently, reducing the time spent deciphering complex logic.
Prioritization and planning
Technical debt assessment: Regularly evaluate the codebase to identify areas of technical debt and assess their severity. This allows for prioritization of debt reduction efforts based on potential impact.
Balancing feature development: While addressing technical debt is vital, ongoing development shouldn't grind to a halt. Striking a balance between debt reduction and feature development is essential for project progress.
Architectural review: Regularly reviewing the system architecture helps identify potential bottlenecks or design flaws that could lead to technical debt. Proactive improvements to the architecture can prevent future issues.
Communication and teamwork
Collective ownership: When developers share responsibility for code quality, they are more likely to identify and address potential technical debt proactively.
Knowledge transfer: Collaborative practices allow experienced developers to share their insights with new and less experienced team members, fostering a culture of code quality and best practices.
Improved problem-solving: By working together, developers can approach technical debt challenges from different perspectives, leading to more effective solutions.
Conclusion
This guide has all the information about tech debt and its audit and prevention. By implementing the above-mentioned strategies, a software development company can avoid the burden of technical debt. This ultimately improves code quality, maintainability, and the development process.