Your code shouldn't look like alien hieroglyphics. Too many cryptic symbols make your code hard to understand and maintain. Your code shouldn't look like alien hieroglyphics. Too many cryptic symbols make your code hard to understand and maintain. Your code shouldn't look like alien hieroglyphics. T Problems with Cryptic Code Readability
Cognitive overload
Maintenance nightmares
Debugging challenges
Learning curve
Unwrapped lines
Hidden defects
Anonymous Functions Abuse Readability Cognitive overload Maintenance nightmares Debugging challenges Learning curve Unwrapped lines Unwrapped lines Hidden defects Anonymous Functions Abuse Anonymous Functions Abuse Solutions Avoid language clever hacks
Prefer meaningful variable names
Extract complex expressions
Use language features wisely
Limit expression complexity Avoid language clever hacks Prefer meaningful variable names Extract complex expressions Use language features wisely Limit expression complexity Refactorings https://hackernoon.com/improving-the-code-one-line-at-a-time?embedable=true https://hackernoon.com/improving-the-code-one-line-at-a-time?embedable=true Context Syntactic noise refers to code constructs that don't directly map to real-world concepts. Syntactic noise While symbols like '{}' are valid syntax in many programming languages, excessive use creates code that looks like abstract art rather than a solution to a problem. When you pack too many operators, brackets, and special characters into a single expression, you force readers to mentally parse complex syntax before understanding what the code does. This disconnect between symbols and real-world meaning makes your code harder to understand, debug, and maintain. Think of your code as a form of communication with other developers (and your future self). Just as excessive punctuation!!! makes text!!?!? hard to read!!! Excessive syntactic noise creates similar barriers in code. Sample Code 📖 Wrong ❌ [](){}

/* This valid lambda function:

Captures no variables.
Takes no arguments.
Performs no actions.

[]: This is the capture clause. 
It specifies which variables from the surrounding scope
are accessible inside the lambda function. 
An empty capture clause [] means the lambda
*does not capture* any variables from the surrounding scope.

(): This is the parameter list. 
It defines the arguments the lambda function accepts. 
An empty () means the lambda takes *no parameters*.

{}: This is the function body. 
It contains the code that the lambda executes when called. 
An empty {} means the lambda has no operations 
to perform—it does nothing.

*/ [](){}

/* This valid lambda function:

Captures no variables.
Takes no arguments.
Performs no actions.

[]: This is the capture clause. 
It specifies which variables from the surrounding scope
are accessible inside the lambda function. 
An empty capture clause [] means the lambda
*does not capture* any variables from the surrounding scope.

(): This is the parameter list. 
It defines the arguments the lambda function accepts. 
An empty () means the lambda takes *no parameters*.

{}: This is the function body. 
It contains the code that the lambda executes when called. 
An empty {} means the lambda has no operations 
to perform—it does nothing.

*/ const result = arr.filter(x => x !== null && x !== undefined)
  .map((y) => ({ val: y.value, meta: 
    y.meta ? y.meta : {default: true}}))
  .reduce((acc, {val, meta}) => 
    meta.default ? acc : [...acc, 
      {processed: val * 2, origin: meta}], [])
  .some(({processed}) => processed > 10 && processed < 50); const result = arr.filter(x => x !== null && x !== undefined)
  .map((y) => ({ val: y.value, meta: 
    y.meta ? y.meta : {default: true}}))
  .reduce((acc, {val, meta}) => 
    meta.default ? acc : [...acc, 
      {processed: val * 2, origin: meta}], [])
  .some(({processed}) => processed > 10 && processed < 50); Right 👉 function isNotNull(x) {
  return x !== null && x !== undefined
  // Another code smell here
}

function mapToValueAndMeta(y) {
  const meta = y.meta ? y.meta : { default: true }
  return { val: y.value, meta }
}

function reduceToProcessedList(acc, { val, meta }) {
  if (meta.default) {
    return acc
  }
  return [...acc, { processed: val * 2, origin: meta }]
}

function isProcessedInRange({ processed }) {
  return processed > 10 && processed < 50
}

// This is more declarative but far from 
// Domian business and too generic
const filtered = arr.filter(isNotNull)
const mapped = filtered.map(mapToValueAndMeta)
const processedList = mapped.reduce(reduceToProcessedList, [])
const result = processedList.some(isProcessedInRange) function isNotNull(x) {
  return x !== null && x !== undefined
  // Another code smell here
}

function mapToValueAndMeta(y) {
  const meta = y.meta ? y.meta : { default: true }
  return { val: y.value, meta }
}

function reduceToProcessedList(acc, { val, meta }) {
  if (meta.default) {
    return acc
  }
  return [...acc, { processed: val * 2, origin: meta }]
}

function isProcessedInRange({ processed }) {
  return processed > 10 && processed < 50
}

// This is more declarative but far from 
// Domian business and too generic
const filtered = arr.filter(isNotNull)
const mapped = filtered.map(mapToValueAndMeta)
const processedList = mapped.reduce(reduceToProcessedList, [])
const result = processedList.some(isProcessedInRange) Detection 🔍 [x]Semi-Automatic [x]Semi-Automatic [x] You can detect syntactic noise by looking for lines with multiple nesting levels of brackets, parentheses, or braces, chained operations that stretch across numerous lines, and expressions that make you pause to count opening and closing symbols. Code that requires horizontal scrolling due to symbol density is another red flag, multiple ternary operators in a single expression, and nested arrow functions with implicit returns. arrow functions implicit returns Modern IDEs and linters can help identify overly complex expressions. ESLint rules like complexity and max-depth flag code with too many nested constructs. The "cognitive complexity" metric in SonarQube also helps identify hard-to-understand code. Exceptions 🛑 Code Optimized by Machines Code Optimized by Machines Tags 🏷️ Complexity Complexity Level 🔋 [x]Intermediate [x]Intermediate [x] Why the Bijection Is Important 🗺️ Code should map one-to-one with the real-world concepts it represents. Each variable, function, and expression should correspond to something tangible in your problem domain. When you clutter code with excessive syntax that doesn't represent real-world entities, you create a disconnect between the problem and solution. Remember that code is written once but read many times. By maintaining a clear bijection between code constructs and real-world concepts, you create software that stays maintainable throughout its lifecycle. bijection real-world AI Generation 🤖 AI code generators sometimes create syntactic noise. When you ask for code with minimal prompt guidance, AI tools frequently optimize for brevity over readability, packing multiple operations into dense one-liners. This approach produces "clever" but hard-to-maintain code with chained methods, nested ternaries, and complex expressions. Modern AI generators like GPT models can also create exceptionally dense code when asked to solve problems in minimal lines, inadvertently producing syntactically noisy solutions. They may not recognize when code crosses the readability threshold without specific instructions to prioritize clarity over conciseness. Please don't prompt this. AI Detection 🥃 AI tools can help detect and fix syntactic noise with appropriate prompting. If you use instructions like "refactor for readability" or "simplify this expression," you will get cleaner code. Try Them! 🛠 Try Them! 🛠 Try Them! 🛠 Remember: AI Assistants make lots of mistakes Remember: AI Assistants make lots of mistakes Suggested Prompt: Remove the syntactic noise and make it more declarative Suggested Prompt: Remove the syntactic noise and make it more declarative Without Proper Instructions

With Specific Instructions



ChatGPT

ChatGPT



Claude

Claude



Perplexity

Perplexity



Copilot

Copilot



Gemini

Gemini



DeepSeek

DeepSeek



Meta AI

Meta AI



Grok

Grok



Qwen

Qwen Without Proper Instructions

With Specific Instructions



ChatGPT

ChatGPT



Claude

Claude



Perplexity

Perplexity



Copilot

Copilot



Gemini

Gemini



DeepSeek

DeepSeek



Meta AI

Meta AI



Grok

Grok



Qwen

Qwen Without Proper Instructions

With Specific Instructions Without Proper Instructions Without Proper Instructions With Specific Instructions With Specific Instructions ChatGPT

ChatGPT ChatGPT ChatGPT ChatGPT ChatGPT ChatGPT ChatGPT Claude

Claude Claude Claude Claude Claude Claude Claude Perplexity

Perplexity Perplexity Perplexity Perplexity Perplexity Perplexity Perplexity Copilot

Copilot Copilot Copilot Copilot Copilot Copilot Copilot Gemini

Gemini Gemini Gemini Gemini Gemini Gemini Gemini DeepSeek

DeepSeek DeepSeek DeepSeek DeepSeek DeepSeek DeepSeek DeepSeek Meta AI

Meta AI Meta AI Meta AI Meta AI Meta AI Meta AI Meta AI Grok

Grok Grok Grok Grok Grok Grok Grok Qwen

Qwen Qwen Qwen Qwen Qwen Qwen Qwen Conclusion 🏁 Syntactic noise is like static interference in communication—technically valid, but gets in the way of understanding. When you prioritize clear code over clever one-liners, you create software that's easier to understand, debug, and maintain. Next time you're tempted to pack multiple operations into a dense expression, remember that you're not just writing for the computer—you're writing for people. Break complex operations into named steps that reflect real-world concepts, and your code will tell a story that everyone can follow. Related Reading https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-ii-o96s3wl4
https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-v-evj3zs9
https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-xxiv
https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-xxi
https://maximilianocontieri.com/code-smell-294-implicit-return
https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-xxiv
https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-xxxiii
https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-xli
https://hackernoon.com/code-smell-236-what-to-do-with-excessively-long-code-lines https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-ii-o96s3wl4 https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-ii-o96s3wl4 https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-v-evj3zs9 https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-v-evj3zs9 https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-xxiv https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-xxiv https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-xxi https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-xxi https://maximilianocontieri.com/code-smell-294-implicit-return https://maximilianocontieri.com/code-smell-294-implicit-return https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-xxiv https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-xxiv https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-xxxiii https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-xxxiii https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-xli https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-xli https://hackernoon.com/code-smell-236-what-to-do-with-excessively-long-code-lines https://hackernoon.com/code-smell-236-what-to-do-with-excessively-long-code-lines More Information 📕 https://martinfowler.com/bliki/SyntacticNoise.html?embedable=true https://martinfowler.com/bliki/SyntacticNoise.html?embedable=true https://en.wikipedia.org/wiki/Syntactic_noise?embedable=true https://en.wikipedia.org/wiki/Syntactic_noise?embedable=true Disclaimer: Code Smells are my opinion. Disclaimer: Code Smells are my opinion. opinion Credits: Photo by Elyas Pasban on Unsplash Credits: Photo by Elyas Pasban on Unsplash Elyas Pasban Unsplash The function of good software is to make the complex appear simple The function of good software is to make the complex appear simple Graciano Cruz Graciano Cruz https://hackernoon.com/400-thought-provoking-software-engineering-quotes?embedable=true https://hackernoon.com/400-thought-provoking-software-engineering-quotes?embedable=true This article is part of the CodeSmell Series on HackerNoon This article is part of the CodeSmell Series on HackerNoon https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-i-xqz3evd?embedable=true https://hackernoon.com/how-to-find-the-stinky-parts-of-your-code-part-i-xqz3evd?embedable=true

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