diff --git a/lectures/optimization/gprof/README.md b/lectures/optimization/gprof/README.md
index 9cfab57..d588c13 100644
--- a/lectures/optimization/gprof/README.md
+++ b/lectures/optimization/gprof/README.md
@@ -57,10 +57,24 @@ int main() {
    $ cat profile.txt
    ```
 
-## Understanding the Output
+## Understanding the Output (in the profile.txt file)
 - **Flat Profile**: Shows execution time spent in each function.
 - **Call Graph**: Displays function call relationships and their execution time.
 
+The profiling results show that heavyComputation() takes significantly more execution time than lightComputation(), even though lightComputation() is called 1000 times.
+The flat profile from gprof also indicates the percentage of time spent in each function, helping to identify bottlenecks. For the above test program, the flat profile is like this:
+
+```plaintext
+Each sample counts as 0.01 seconds.
+  %   cumulative   self              self     total
+ time   seconds   seconds    calls  ms/call  ms/call  name
+ 85.71      0.24     0.24        1   240.00   240.00  heavyComputation()
+ 14.29      0.28     0.04     1000     0.04     0.04  lightComputation()
+  0.00      0.28     0.00        1     0.00     0.00  __static_initialization_and_destruction_0(int, int)
+```
+
+Note: The __static_initialization_and_destruction_0(int, int) function is generated by the compiler during the static initialization and destruction phases of a program, particularly for global or static variables.
+
 ## Best Practices for Using `gprof`
 - Use `-O2` optimizations but **avoid `-O3`**, which may inline functions and reduce profiling accuracy.
 - Profile with realistic input data to get meaningful results.