Duplication in Programming: When to Allow | Generated by AI
Question: Is it impossible to avoid duplicates entirely in programming? When should we intentionally allow duplicates, and when should we eliminate them? For example, in a string like “abc”, removing duplicate letters like ‘a’ would make it harder to read or construct certain words.
Answer:
In programming, it is practically impossible to completely avoid all forms of duplication, and that’s not always desirable. Duplication (or repetition) is a natural and often necessary part of code and data. The key is distinguishing between beneficial duplication (which improves clarity, performance, or expressiveness) and harmful duplication (which leads to maintenance issues, bugs, or inefficiency).
When we should intentionally allow or introduce duplicates:
- For readability and expressiveness
Repeating values or patterns makes intent clearer.- Example: The string
"Mississippi"naturally contains duplicate letters (‘s’, ‘i’, ‘p’). Removing duplicates to get"Misp"destroys meaning and readability. - In code: Repeating a constant like
0multiple times in an array initialization[0, 0, 0, 0]is clearer than trying to abstract it unnecessarily.
- Example: The string
-
Data that inherently contains repetition
Real-world data often has duplicates: logs, user inputs, measurements, text, etc. Removing them prematurely can lose important information (e.g., word frequency in text analysis). -
Performance reasons
Denormalization in databases intentionally introduces duplicates to avoid expensive joins and improve query speed. -
Simple algorithms or early prototypes
A small amount of copied code is acceptable when the logic is unstable or the duplication is minimal. Premature abstraction can make code harder to understand. - When abstraction adds complexity
Trying to eliminate every repeated character or value can lead to overly complex code. For example, generating"hello"without repeating any letter is impossible in English while keeping it meaningful.
When we should eliminate duplicates:
-
Configuration and magic values
Repeated hardcoded values (e.g.,42scattered across code) should be extracted into named constants. - Repeated logic (DRY principle)
The most common harmful duplication: identical or similar code blocks in multiple places. Changing one requires changing all → bugs.- Refactor into functions, classes, modules, or templates.
- Data processing where uniqueness matters
- Converting a list to a set to remove duplicates when order doesn’t matter and uniqueness is required (e.g., unique user IDs).
- Deduplicating records in databases or datasets.
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Large-scale maintenance
When the same pattern appears in many places and is likely to change, abstraction (functions, loops, higher-order functions, macros) reduces future effort. - Memory or storage efficiency
In resource-constrained environments, removing unnecessary duplicates saves space (e.g., string interning, flyweight pattern).
Summary guideline:
- Allow duplicates when they carry meaning, improve clarity, or when removing them adds unnecessary complexity.
- Eliminate duplicates when they are accidental, represent the same concept in multiple places, or cause maintenance/scalability issues.
Your "abc" example is perfect: if the string represents a word or message, duplicate letters are not only allowed but required for correct meaning. Only remove duplicates when the problem explicitly requires uniqueness (e.g., “find distinct characters” or “unique username check”).
In short: Duplication is not inherently bad. Thoughtful repetition often makes code and data more human-friendly. Blindly applying “no duplicates ever” leads to convoluted, hard-to-read solutions. Apply the DRY principle judiciously, not dogmatically.