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Premature Memoization: How to Properly Apply It - Code Smell 250by@mcsee
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Premature Memoization: How to Properly Apply It - Code Smell 250

by Maximiliano ContieriMay 1st, 2024
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Too Long; Didn't Read

This article is part of the Code Smell Series of the Hackernoon Series. The article is about Premature Optimization. The TL;DR: Don't apply [premature optimization] too early. It can help you improve the performance of recursive functions involving redundant computations but compromise code readability.
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Memoization is awesome. Let's abuse it.

TL;DR: Don't apply premature optimization too early

Problems

  • Readability
  • Code Complexity
  • Premature Optimization
  • Obscured Logic

Solutions

  1. Apply memoization in actual real business situations, and measure its impact through empirical benchmarks.

Context

Memoization can help you improve the performance of recursive functions involving redundant computations but compromise code readability and maintainability.


It would help if you only used it with strong factual evidence on real business case scenarios.

Sample Code

Wrong

memo = {}
def factorial_with_memo(n):
    if n in memo:
        return memo[n]
    if n == 0:
        return 1
    result = n * factorial_with_memo(n-1)
    memo[n] = result
    return result
  
  # This function optimizes the computation of factorials
  # by storing previously computed values,
  # reducing redundant calculations 
  # and improving performance for large inputs.

Right

def factorial(n):
    if n == 0:
        return 1
    return n * factorial(n-1)

Detection

  • [x]Semi-Automatic

You can search for all places where you are using this technique and validate if they are worth it.

Exceptions

  • Real performance problems with strong factual evidence

Tags

  • Premature Optimization

Level

  • [x]Intermediate

AI Generation

Unless you explicitly ask the IAs to use this technique, they will suggest cleaner solutions.

AI Detection

ChatGPT, Gemini, and Claude.ai detect some problems with this technique but do not mention readability as a concern.

Conclusion

It would be best if you kept a balance between performance optimization and code clarity.


You can consider alternatives such as iterative approaches or algorithmic optimizations since memoization significantly compromises code readability.

Relations

Code Smell 06 - Too Clever Programmer

Code Smell 20 - Premature Optimization

More Info

Wikipedia

Disclaimer

Code Smells are my opinion.

Credits

Photo by Steffen Lemmerzahl on Unsplash


A cache with a bad policy is another name for a memory leak.

Rico Mariani

Software Engineering Great Quotes


This article is part of the CodeSmell Series.


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