12 Toxic Coding Habits That Destroy Readability (And How to Avoid Them)

1. Splitting Microservices One Table per Service

The programmer "Er Gou" embraces microservices to the extreme, creating a separate service for each database table, believing it improves independence and allows new technologies like JDK 21. In practice, this leads to a complex architecture, numerous RPC calls, version conflicts, and a burdensome deployment process for newcomers.

2. Refactoring Without Production Rollout

Er Gou adds a feature flag to reduce RPC calls and marks the new logic with a comment "new logic". However, the flag is only enabled in the test environment, causing confusion when the new code is merged but not activated in production, leading to failed deployments and overtime work.

3. Writing Methods Longer Than 1000 Lines

Believing that longer methods are more coherent and showcase skill, Er Gou writes massive methods and never extracts smaller functions, making the code hard to understand and slowing down new developers.

4. Nesting More Than Ten Levels of if/try/else

Er Gou nests deep conditional structures, receiving praise for "high code quality" despite the code being unreadable; newcomers struggle to comprehend and maintain such code.

5. Random Variable Naming Unrelated to Business Logic

Variables are named arbitrarily (e.g., str1, list2) to treat coding as art, which later leads to memory loss about their purpose and hampers maintenance.

6. Adding Incorrect or Misleading Comments

Comments are deliberately altered to convey wrong meanings, swapping phrases like "yes" to "no" and "better" to "worse", confusing anyone who relies on them.

7. Changing Code Without Updating Comments

Even after extensive code modifications, comments remain unchanged, resulting in mismatched documentation that misleads developers.

8. Copy‑Pasting Code Repeatedly

Er Gou frequently copies existing code blocks instead of refactoring, causing duplicated logic, hidden bugs, and increased workload for newcomers who must track all copies.

9. Writing Detailed Technical Specs but Ignoring Them in Implementation

Extensive design documents and diagrams are produced, yet the actual implementation deviates (e.g., using a simple Redis sync instead of a sophisticated inventory system), leaving newcomers confused.

10. Refusing to Add Logging

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

11. Introducing Heavy Frameworks to Solve Simple Problems

Er Gou adopts complex rule‑engine frameworks (Drools, SPEL, etc.) to replace a straightforward strategy pattern, complicating the codebase and increasing the learning curve for new developers.

12. Reinventing the Wheel

Instead of using proven libraries (e.g., Redisson for distributed locks), Er Gou builds custom solutions with SETNX, leading to bugs but providing personal learning experience.

Summary

The twelve practices above illustrate how poor decisions—over‑engineering, excessive refactoring, unreadable code, and neglecting best practices—significantly reduce code readability and increase maintenance difficulty. Developers should avoid these pitfalls and follow clean‑code principles.