Developers spend an average of 42 hours at work each week, out of which 13.4 hours are spent on technical debt. This when viewed from the allocated budget for developer’s salary comes out as a significant part of finances going to a non-productive task. Leveraging process and tools to measure technical debt is often a part of a compromised strategy that further bears on the efficiency and cost-effectiveness of service delivery.
A study by Gartner highlights that in 2023, I&O leaders who will actively manage and reduce the technical debt in companies will be able to achieve their service delivery time 50% faster. This also aligns with the productivity of engineers, as when the debt will be dealt with proactively, it will free up the developers to focus more on the strategic business goals.
What is Technical Debt?
Technical Debt is referred to the cost incurred due to unresolved issues, including bugs that will affect them in future and require reworking, thus affecting the finances of the company, productivity of engineers, affect time-to-market and will cause customer dissatisfaction.
This debt takes form in two ways:
- Planned Technical Debt: This happens when the developer chooses to build the code and implement it quickly to establish a market presence while compromising on the quality of the delivery output.
- Inadvertent Technical Debt: This happens when a developer does not fully understand the market requirements and their inexperience or mismanagement contribute to code errors.
How does Technical Debt affect Businesses?
Developers while creating and implementing a code have to always balance the challenges of putting out a clean, well-designed code that is good enough for future iterations, leaves space for innovations, and brings customer satisfaction after delivery. However, the evolving and competitive business environment demands tight-deadline delivery, effective process and tools to measure technical debt while offering limited resources to developers to design and develop the required “perfect code”. Thus technical debt emerges due to the gap generated between requirements of an app, software or system and the code generated to bring that to reality.
Needless to say, technical debt tends to accumulate interest that becomes tiresome and difficult to rework as it continues to cumulate. This has significant implications on business operations, productivity, efficiency, financials and reputation.
Technical Debt Implications on Businesses
- Increased Cost: As businesses need to spend countless hours on fixing unattended issues or shortcuts taken during the development phase, it will only add to the existing operational cost.
- Low Service Quality: With the debt accumulating, when problems are not addressed at the development phase itself, it is more likely to cause software malfunctions. This will raise challenges in smooth software updates, exposing the system to bugs, security risks and even crashes.
- Challenges in Scaling Operations: When the issues are not resolved at the development stage, it makes the upgrade process on the app and software highly challenging. Hence, the need for process and tools to measure technical debt becomes even more important.
- Reputation Damage: When the service quality drops, issues continue to pile up and operations become incapable of scaling as the technology grows, it disrupts customer service, eventually affecting the company’s reputation.
- Hindered Innovation: When more time is spent on fixing accumulated bugs and other issues, there is less time left with developers to focus on innovations that can help the company be efficient and scale heights.
- Increase in Time-to-Market: With an interest generated on debt, developers have to address the piled up issues which obstruct the time-to-market for the app, software or product.
Categories of Process and Tools to Measure Technical Debt?
- Static Code Analysis
Sometimes developers have to accept the necessity that focusing on business value delivery is more important than delivering optimal quality code. While code quality is considered subjective, a good quality code can be described as the one that is clean and can stand the test of time. Static code analysis tools allow developers to understand the quality of their code, review unit test coverage and identify potential bugs. This process and tools to measure technical debt offer a set of customizable rules and techniques. - Software Composition Analysis
Software composition analysis (SCA) tools analyze the software packages as well as libraries for any vulnerabilities and provide remediation suggestions. Software engineers need to focus on the building blocks that should be used, including frameworks, software languages and open-source software & libraries. As the development phase progresses, these building blocks are sometimes abandoned by the developers or they become obsolete or carry in them security vulnerabilities. When these building blocks stop serving its intended purpose, it starts becoming debt. SCA process and tools to measure technical debt offer a comprehensive view of these blocks to identify compliance issues or potential vulnerabilities. - Software Architecture Technical Debt Analysis
Software Architecture Analysis tools help developers to monitor and measure the debt in the system architecture. Since architecture debt has a much more significant impact on the product quality than the others and it is also the most difficult to fix. This process and tools to measure technical debt, map the system architecture visually with its dependencies and cross-references to obtain the overall score and separate the issues. - Performance and Observability Analysis
Performance and Observability Analysis tools help engineers observe the system’s logs, performance, errors or warnings during the runtime of the application. However, these tools tend to generate massive amounts of data, hence automation of log analysis, early performance analysis, record keeping and dashboard creation is recommended. - Static Security and Vulnerability Analysis
Software engineers who work on code development don’t always have the training, expertise or skills to identify security vulnerabilities, before the code becomes a debt and starts affecting the productivity and adding to the costs. Static Application Security Testing (SAST) tools when used in the code development cycle can catch such vulnerabilities early on. While these process and tools to measure technical debt are not a silver bullet, they do focus on the OWASP top ten vulnerabilities to analyze the source and binary code for security issues in the development phase itself.
How to Select the Technical Debt Measurement Tools?
When evaluating process and tools to measure technical debt and monitor it at the code level, software engineering leaders must include the following criteria:
- Technology and language: Not all tools are equally suitable for different software development languages.
- Software engineering stack: Different stacks, such as Spring Boot (Java), NodeJS (JavaScript), Microsoft .NET (for example, C#), will require different tools due to the nature of the technology used to implement the stacks.
- Depth and breadth of data: Assess the tool’s ability to provide data on code smells, vulnerabilities, test coverage and an overall debt score.
- Delivery model (SaaS versus on-premises): Some tools do not support the SaaS model and therefore must be run in-house. Usually, such tools can be deployed on-premises and support containerization for cloud deployment. However, these tools typically require more effort to install, configure and maintain. Last but not least, take into account potential security risks associated with exposing code that contains company secrets (for example, proprietary algorithms).
- Integration capabilities: Determine how well the tool will integrate into the software development life cycle and other relevant systems.
- License cost: When selecting tools, don’t underestimate the license cost and the cost of maintenance agreements.
Technical debt is not all-encompassing, rather is incurred on companies when developers intentionally or unintentionally choose to delay better coding. But this choice of ignoring certain pieces that might seem unimportant at the moment can accumulate to obstruct innovations, future developments and timely delivery.
Technical debt is the leading cause of countless hours spent as productivity loss, bugs and issues that impact your business’s customer experience. Organizations must identify the key pieces of debt that get in their way of reaching business objectives. Moreover, identifying the ideal process and tools to measure technical debt and analyze it based on your requirements forms the core of an effective, efficient, cost-effective, and high-quality service delivery.
