From b5a8149e8556914d26e9e29f5955b9130912d35b Mon Sep 17 00:00:00 2001
From: ajfAfg <56056962+ajfAfg@users.noreply.github.com>
Date: Tue, 5 Mar 2024 12:51:15 +0900
Subject: [PATCH] Write README about the benchmark

---
 .../README.md                                 | 21 +++++++++++--------
 1 file changed, 12 insertions(+), 9 deletions(-)

diff --git a/benchmarks/measure_execution_time_of_function_that_solve_optimal_supervision_tree/README.md b/benchmarks/measure_execution_time_of_function_that_solve_optimal_supervision_tree/README.md
index 46e8296..30b74e6 100644
--- a/benchmarks/measure_execution_time_of_function_that_solve_optimal_supervision_tree/README.md
+++ b/benchmarks/measure_execution_time_of_function_that_solve_optimal_supervision_tree/README.md
@@ -1,14 +1,17 @@
-measure_execution_time_of_function_that_solve_optimal_supervision_tree
-=====
+# Benchmark to measure the execution time of the function to solve an optimal supervision tree
 
-An escript
+Benchmark to verify that the proposed algorithm is fast enough for many realistic cases. In the experiment, a randomly generated graph is input to the proposed algorithm and the execution time is measured. The number of vertices and edges are varied, with the number of vertices varying from 10, 20, ..., 70, and the number of edges is 1, 2, or 3 times the number of vertices. 100 trials are performed for each variable combination.
 
-Build
------
+The benchmark is run as follows:
 
-    $ rebar3 escriptize
+```sh
+./benchmark
+```
 
-Run
----
+The benchmark program outputs a CSV file that records the number of vertices and edges and the execution time. The experimental results can be converted to a figure as follows:
 
-    $ _build/default/bin/measure_execution_time_of_function_that_solve_optimal_supervision_tree
+```sh
+python3 generate_figure.py
+```
+
+The figure also displays the median time for each number of vertices.