From 8ccab7f2543e9a5ad6ccf1a95a3d93139daff97a Mon Sep 17 00:00:00 2001
From: Enlightenus <88682809+Enlightenus@users.noreply.github.com>
Date: Wed, 24 Jul 2024 19:40:11 -0700
Subject: [PATCH] Update time_complexity.md

Update first paragraph to avoid confusion between time complexity and run time
---
 en/docs/chapter_computational_complexity/time_complexity.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/en/docs/chapter_computational_complexity/time_complexity.md b/en/docs/chapter_computational_complexity/time_complexity.md
index c29bfd5b8..c634b04a6 100644
--- a/en/docs/chapter_computational_complexity/time_complexity.md
+++ b/en/docs/chapter_computational_complexity/time_complexity.md
@@ -1,6 +1,6 @@
 # Time complexity
 
-Time complexity is a concept used to measure how the run time of an algorithm increases with the size of the input data. Understanding time complexity is crucial for accurately assessing the efficiency of an algorithm.
+We can directly and accurately assess the efficiency an algorithm by measuring the run time. How to accurately assess the run time of an algorithm?
 
 1. **Determining the Running Platform**: This includes hardware configuration, programming language, system environment, etc., all of which can affect the efficiency of code execution.
 2. **Evaluating the Run Time for Various Computational Operations**: For instance, an addition operation `+` might take 1 ns, a multiplication operation `*` might take 10 ns, a print operation `print()` might take 5 ns, etc.