12 Toxic Coding Habits That Destroy Readability and Maintenance

1. One table per microservice

The author describes a programmer who enthusiastically applies microservice principles to the extreme, creating a separate service for every database table. While this seems to promote independent deployment, it leads to a tangled architecture with countless RPC calls, versioning headaches, and a steep learning curve for newcomers.

2. Refactoring without production rollout

The same programmer adds a feature flag to reduce RPC traffic but only enables it in the test environment. When the flag is not turned on in production, downstream developers encounter failures because they assume the new logic is active, leading to wasted effort and delayed releases.

3. Writing excessively long methods

He believes that longer methods are more coherent and that a skilled developer should write methods exceeding a thousand lines. This results in monolithic code blocks that are hard to understand, test, or modify.

4. Deeply nested control structures

He frequently nests ten or more layers of if/else or try/catch statements, claiming the code quality is high. However, new team members find such nesting incomprehensible and error‑prone.

5. Random, meaningless variable names

Variables are named arbitrarily (e.g., str1, list2) without reflecting business meaning. The programmer can remember them, but after a few weeks the names lose their purpose, making future maintenance difficult.

6. Introducing misleading comments

Comments are deliberately altered to convey the opposite meaning or swapped between unrelated sections, confusing anyone who relies on them for understanding the code.

7. Changing code but never updating comments

When the code is heavily refactored, the original comments remain unchanged, causing a mismatch between implementation and documentation.

8. Blind copy‑and‑paste coding

To save time, the programmer copies existing code snippets without adapting them, leading to duplicated logic and hidden bugs that surface during later modifications.

9. Writing detailed technical designs that are ignored in implementation

Extensive design documents (e.g., a complex Redis‑based flash‑sale system) are produced, but the actual code follows a much simpler, unrelated approach, leaving newcomers confused by the discrepancy.

10. Refusing to add logging

Confident in his code, the programmer never adds logs. When a production incident occurs, the lack of logs hampers debugging, forcing a rushed addition of logging after the fact.

11. Over‑engineering with heavyweight frameworks for simple problems

He introduces sophisticated rule‑engine frameworks (Drools, SPEL, etc.) to solve trivial strategy‑selection tasks, increasing system complexity without clear benefit.

12. Reinventing the wheel

He prefers building custom solutions—such as a home‑grown distributed lock using SETNX —instead of using proven libraries like Redisson, which can introduce subtle bugs.

Conclusion

The twelve practices listed above are typical ways to reduce code readability and increase maintenance difficulty. Developers should avoid these anti‑patterns and adopt clearer, more maintainable coding habits.

Programmers like the one described are common; the lessons apply broadly.

Avoid emulating these habits; they hinder long‑term project health.