When 100% Test Coverage Isn’t Enough

📰 Medium · Data Science

100% test coverage isn't enough to ensure code quality, learn how to improve testing with concrete examples

intermediate Published 12 Apr 2026
Action Steps
  1. Write a test suite for the clean_text function using a testing framework like unittest
  2. Use a code coverage tool like coverage.py to measure test coverage
  3. Identify edge cases and write additional tests to cover them
  4. Use a testing library like hypothesis to generate test cases and improve test coverage
  5. Refactor the clean_text function to make it more testable and maintainable
Who Needs to Know This

Developers and QA engineers can benefit from understanding the limitations of test coverage and how to write more effective tests to ensure code quality

Key Insight

💡 Test coverage is not a perfect measure of code quality, and writing effective tests requires considering edge cases and using the right tools

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💡 100% test coverage isn't enough! Learn how to improve testing with concrete examples #testing #codequality

Key Takeaways

100% test coverage isn't enough to ensure code quality, learn how to improve testing with concrete examples

Full Article

Title: When 100% Test Coverage Isn’t Enough

URL Source: https://medium.com/@oral.ersoy.dokumaci/when-100-test-coverage-isnt-enough-9faed3a2875c?source=rss------data_science-5

Published Time: 2026-04-12T19:50:25Z

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# When 100% Test Coverage Isn’t Enough | by Oral Ersoy Dokumaci | Apr, 2026 | Medium

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# When 100% Test Coverage Isn’t Enough

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## Introduction

Suppose you are working in NLP or AI like half of the world including myself. You want to do some text cleaning to prepare training data for a multi-language model. Your goal is to remove text with duplicate meaning within each language. So you “write” a quick cleaning function, even dusting off the ancient language of regex that was once known to humans but only spoken by LLMs these days.

import re

def clean_text(text: str) -> str:

"""Normalize text for dedup."""

text = text.strip()

text = text.lower()

text = re.sub(r"\s+", " ", text) # collapse whitespace

text = re.sub(r"[^\w\s]", " ", text) # replace punctuation

return text
You run the function on an example input.

$ python -c "from preprocess import clean_text; print(clean_t
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