Accumulation of technical debt is a cost driver in advanced projects. Here are some tips to reduce them

Technical debt is a metaphor commonly used in computer science for the potential consequences of poor technical implementation of software.

For bad software design, the effect of accumulated technical debt is similar to what Martin Fowler described in “.design endurance hypothesis,

In shorter sentences, the result is increased time to implement the new functionality. And adding functionality becomes hard. The result is more effort, more cost, increased system instability, more crashes, more bugs, complexity, etc.

restructuring

The most important thing to do to reduce technical debt is regular refactoring of your software.

Broadly speaking, the software development process consists of two stages:
1. Meet the requirements and commission the software
2. Optimize and clean the code

In many projects, the deadline is met with point 1 being met. For point 2, there is often no time to optimize and clean up the code. The result is that after a few years, the software systems of these projects are difficult to maintain.

In modern Scrum projects, the issue is that a Scrum Master is often focused on the delivery of new functionality.

If your scrum master sees reducing technical debt and/or refactoring time as technical stuff that is not relevant to the Product Owners, then you are really in trouble.

The same applies when your product owner thinks it’s technical stuff and isn’t interested in the refactoring results.

One possibility is to measure the improvements of refactoring. This can result in fewer lines of code, improved response times of your application, fewer bugs, and fewer escalation meetings.

Also it can result in lower infrastructure cost. In the end, most optimizations should be measurable in money.

For refactoring, you can also use tools that show potential improvement areas. is a potential tool for showing potential for improvement sonarcube,

Using software analysis tools

Today there are many tools to analyze code quality. A good possibility is to incorporate these tools into your delivery pipeline and let it run for every change.

The advanced level is that the tools are used by your developers on their local workstations, and checks are done every change. The reason is that the sooner a quality problem is detected, the cheaper it is to fix it.

There are various areas for scanning by the tool:

code lining

Lining is important to reduce errors and improve the overall quality of your code. Using lint tools can help you speed up development and reduce costs by producing clean code. If the code is clean, the risk of bugs is reduced.

There are also code linters available for Dockerfiles, configuration files, etc.

quality scanner

SonarQube is an option, and you can add to your pipeline as well. SonarQube is also supported by integration tools such as GitLab.
https://docs.sonarqube.org/latest/analysis/gitlab-integration/

security scanner

It is recommended to check the packages and dependencies you use. Fixing newly found security issues often requires replacing versions with updates. Various tools are available, such as Mend, formerly Whitesource, strongeither Open Source Security Management Snyk,

There are lots of other scanners. Maybe you know better.

audit scanner

Some platforms provide functionality to verify the quality of your code based on a specific language. to like npm audit Node.js or Java tools like . for Jarchitecture, Also, for Python, several static code analysis tools are available.

A helpful way to prove the quality of your software system is to ask others for reviews and their opinions. Exchange and communication lead to learning and improvement.

One easy way out is code reviews. The problem with peer code reviews is often a lack of time and understanding of how to conduct an effective code review. For novices, a list of important points to look for can be helpful.

You can add an advanced developer to your team with the core task of doing reviews. This can improve the quality.

If you work in a company with more teams and developers, you can ask for a review from another team. Some large companies have specialized teams for review and audit.

An external audit can be extremely eye-opening if it is worth it to your management. Typically, an external audit team needs the support of members of your development team.

The process is that they explain the system and provide the code. The audit specialized company often has more advanced analysis software. Additionally, there are interviews with members of the developer team.

The result is a report of the quality status of your software system and areas of improvement, as well as a presentation of the results to the developer team with a list of indications for improvement.

The use of software patterns usually reduces technical debt.

For example, using Model-view-presenter (MVP) pattern, This pattern takes advantage of modularity, testability, and a clean and maintainable codebase.

There are lots of clean code patterns. Here are a few ideas:

If you want more, you can look into SOLID principles for clean code.

As you can see from the previous chapter, the number of patterns and principles is huge. It is nearly impossible for a developer team to focus their attention on the most relevant patterns and principles to develop and improve a specific software system.

Support can be provided to the developer’s team with specific guidelines for the specific development project.

Developer guidelines should be as concise as possible and focus on key aspects. It may be that what principles and patterns are relevant to the specific project, such as:

• code conventions, naming conventions
• How to handle test-driven development and exceptions
• Language for comments, classes, etc.
• Rules for standard commit messages
• Code quality scanners for your software systems and their configurations
• using pair programming
• and many more

If you’d like to have some idea of ​​what might be part of the developer guidelines, you can find some pointers here:

Using architecture principles can help reduce technical debt because it gives developer teams general rules and guidelines for how to use IT resources, from a high-level perspective.

An example of a software architecture principle is the API first principle that results in a software system being more easily integrated into other software systems. The result is flexibility. The technical implications are that the design needs to be adapted to provide the API.

Another principle is to reduce complexity. Complexity can be found in software design, functionality to be provided and infrastructure used. Complexity can also be reduced by clean code. Refactoring to reduce complexity results in easier operation of systems in production with fewer problems.