state2gantt + LIBAFL_EDGES_MAP_SIZE_IN_USE

flake.nix

@@ -67,6 +67,7 @@
           export LIBAFL_QEMU_DIR=$(pwd)/qemu-libafl-bridge
           export CUSTOM_QEMU_NO_BUILD=1
           export CUSTOM_QEMU_NO_CONFIGURE=1
+          export LIBAFL_EDGES_MAP_SIZE_IN_USE=1048576
           # export EMULATION_MODE=systemmode
           # export CPU_TARGET=arm
           # export CROSS_CC=arm-none-eabi-gcc

state2gantt/driver.sh

@@ -0,0 +1,7 @@
+#!/bin/sh
+if [ -z "$1" ]; then exit 1; fi
+OFILE_A="$(dirname "$1")/$(basename -s .trace.ron "$1")_a.csv"
+OFILE_B="$(dirname "$1")/$(basename -s .trace.ron "$1")_b.csv"
+~/code/FRET/state2gantt/target/debug/state2gantt $1 "$OFILE_A" "$OFILE_B"
+# ~/code/FRET/state2gantt/plot.r "$OFILE_A" html
+~/code/FRET/state2gantt/plot_response.r "$OFILE_A" "$OFILE_B" html

state2gantt/plot.r

@@ -1,9 +1,13 @@
+#!/usr/bin/env Rscript
 # Load necessary libraries
 library(ggplot2)
 library(readr)
 library(dplyr)
 library(plotly)
 
+QEMU_SHIFT<-5
+TIMESCALE<-1000000
+
 # Function to create a Gantt chart with dots on short segments
 create_gantt_chart <- function(csv_file, MIN_WIDTH, output_format = NULL) {
   # Read the CSV file
@@ -11,8 +15,8 @@ create_gantt_chart <- function(csv_file, MIN_WIDTH, output_format = NULL) {
   
   # Ensure start and end columns are treated as integers
   df <- df %>%
-    mutate(start = as.integer(start),
-           end = as.integer(end))
+    mutate(start = (as.integer(start) * 2**QEMU_SHIFT)/TIMESCALE,
+           end = (as.integer(end) * 2**QEMU_SHIFT)/TIMESCALE)
   
   # Calculate the segment width
   df <- df %>%
@@ -65,5 +69,5 @@ if (length(args) < 1 || length(args) > 2) {
   }
 }
 
-MIN_WIDTH <- 100 # You can set your desired minimum width here
+MIN_WIDTH <- 500 # You can set your desired minimum width here
 create_gantt_chart(csv_file, MIN_WIDTH, output_format)

state2gantt/plot_gantt.py

@@ -0,0 +1,29 @@
+import plotly.figure_factory as ff
+import plotly.express as px
+import pandas as pd
+import sys
+
+def create_gantt_chart(csv_file):
+    # Read the CSV file
+    df = pd.read_csv(csv_file)
+    df.sort_values(by='prio', inplace=True, ascending=False)
+
+    # Prepare the data for the Gantt chart
+    gantt_data = [
+        dict(Task=row['name'], Start=row['start'], Finish=row['end'], Priority=row['prio'])
+        for _, row in df.iterrows()
+    ]
+
+    # Create the Gantt chart
+    fig = ff.create_gantt(gantt_data, group_tasks=True)
+    
+    # Show the Gantt chart
+    fig.write_html("plot.html")
+
+if __name__ == "__main__":
+    if len(sys.argv) != 2:
+        print("Usage: python script.py <csv_file>")
+        sys.exit(1)
+    
+    csv_file = sys.argv[1]
+    create_gantt_chart(csv_file)

state2gantt/plot_response.r

@@ -0,0 +1,89 @@
+#!/usr/bin/env Rscript
+# Load necessary libraries
+library(ggplot2)
+library(readr)
+library(dplyr)
+library(plotly)
+
+QEMU_SHIFT<-5
+TIMESCALE<-1000000
+
+# Function to create a Gantt chart with dots on short segments
+create_gantt_chart <- function(csv_file_a, csv_file_b, MIN_WIDTH, output_format = NULL) {
+  # Read the CSV file
+  df <- read_csv(csv_file_a)
+  # df_b <- read_csv(csv_file_b)
+  df_b <- read_csv(csv_file_b, col_types = cols(.default = "d", name = col_character()))
+  # df <- df %>% bind_rows(df_b)
+  
+  # Ensure start and end columns are treated as integers
+  df <- df %>%
+    mutate(start = (as.integer(start) * 2**QEMU_SHIFT)/TIMESCALE,
+           end = (as.integer(end) * 2**QEMU_SHIFT)/TIMESCALE)
+
+  df_b <- df_b %>%
+    mutate(start = (as.integer(start) * 2**QEMU_SHIFT)/TIMESCALE,
+           end = (as.integer(end) * 2**QEMU_SHIFT)/TIMESCALE)
+  
+  # Calculate the segment width
+  df <- df %>%
+    mutate(width = end - start)
+  
+  # Sort the DataFrame by 'prio' column in descending order
+  df <- df %>%
+    arrange(prio)
+  
+  # Create the Gantt chart with ggplot2
+  p <- ggplot(df, aes(x = start, xend = end, y = reorder(name, prio), yend = name)) +
+    geom_segment(aes(color = factor(prio)), size = 6) +
+    labs(title = "Gantt Chart", x = "Time Step", y = "Task", color = "Priority") +
+    theme_minimal()
+
+  # Plot Ranges
+  p <- p + geom_segment(data = df_b, aes(color = factor(prio)), size = 1)
+
+  p <- p + geom_point(data = df_b, 
+                      aes(x = end, y = name), 
+                      color = "blue", size = 2)
+
+  # Add dots on segments shorter than MIN_WIDTH
+  p <- p + geom_point(data = df %>% filter(width < MIN_WIDTH), 
+                      aes(x = start, y = name), 
+                      color = "red", size = 1)
+  
+  
+  # Convert the ggplot object to a plotly object for interactivity
+  p_interactive <- ggplotly(p)
+  
+  # Handle output format
+  if (!is.null(output_format)) {
+    output_file <- sub("\\.csv$", paste0(".", output_format), csv_file_a)
+    if (output_format == "html") {
+      htmlwidgets::saveWidget(p_interactive, output_file)
+    } else if (output_format == "png") {
+      ggsave(output_file, plot = p, device = "png")
+    } else {
+      stop("Invalid output format. Use 'html' or 'png'.")
+    }
+  } else {
+    # Print the interactive Gantt chart
+    print(p_interactive)
+  }
+}
+
+# Main execution
+args <- commandArgs(trailingOnly = TRUE)
+if (length(args) < 2 || length(args) > 3) {
+  stop("Usage: Rscript script.R <csv_file> <csv_file> [output_format]")
+} else {
+  csv_file_a <- args[1]
+  csv_file_b <- args[2]
+  if (length(args) == 3) {
+    output_format <- args[3]
+  } else {
+    output_format <- NULL
+  }
+}
+
+MIN_WIDTH <- 500 # You can set your desired minimum width here
+create_gantt_chart(csv_file_a, csv_file_b, MIN_WIDTH, output_format)