Replace the composition chart with a probability chart that actually sums to 100%

2026-08-17 23:40:30 +02:00
parent 2c622b482b
commit bf94e83738
4 changed files with 47 additions and 30 deletions
@@ -0,0 +1,120 @@
+library(ggplot2)
+library(dplyr)
+library(readr)
+library(stringr)
+library(tidyr)
+
+# Usage: Rscript combined_fault_probability.r exp_abspath1 ... resultsdata_file
+#
+# Divides by the faultspace area instead of by a marker total, which makes the
+# running modes comparable: raw counts scale with how long WAMR runs, so they
+# say more about execution length than about susceptibility.
+#
+# Each segment is P[outcome] for a uniformly random single-bit flip in the
+# traced fault space, so a bar's height is P[anything goes wrong].
+#
+# Replaces combined_fault_composition.r, which divided by the marker total and
+# was therefore this chart with every bar rescaled to 100%.
+
+args <- commandArgs(trailingOnly = TRUE)
+if (length(args) < 2) {
+  stop("Need at least 2 experiments")
+}
+
+csv_suffix <- if (grepl("\\.csv$", args[length(args)])) {
+  args[length(args)]
+} else {
+  "resultsdata.csv"
+}
+exp_args <- if (grepl("\\.csv$", args[length(args)])) {
+  args[-length(args)]
+} else {
+  args
+}
+
+extract_info <- function(path) {
+  dir_name <- basename(path)
+  match <- str_match(
+    dir_name,
+    "^\\d{2}-\\d{2}_\\d{2}-\\d{2}-\\d{2}_(.+?)_(c|aot|interp)_"
+  )
+  if (is.na(match[1, 1])) {
+    warning(paste("Could not parse:", dir_name))
+    return(NULL)
+  }
+  list(base_name = match[1, 2], variant = match[1, 3], path = path)
+}
+
+# Load data
+all_data <- data.frame()
+
+for (arg in exp_args) {
+  info <- extract_info(arg)
+  if (is.null(info)) {
+    next
+  }
+
+  csv_file <- file.path(info$path, csv_suffix)
+  if (!file.exists(csv_file)) {
+    warning(paste("Missing:", csv_file))
+    next
+  }
+  df <- read_csv(csv_file, col_types = cols())
+  df$base_name <- info$base_name
+  df$variant <- info$variant
+  all_data <- bind_rows(all_data, df)
+}
+
+# TODO: Finally put all the bullshit before this in some shared space
+
+if (nrow(all_data) == 0) {
+  stop("No data loaded")
+}
+
+marker_order <- c(
+  "OK_MARKER",
+  "DETECTED_MARKER",
+  "GROUP1_MARKER",
+  "TRAP",
+  "TIMEOUT",
+  "WRITE_TEXTSEGMENT",
+  "ACCESS_OUTERSPACE",
+  "FAIL_MARKER"
+)
+
+# Don't merge GROUP1_MARKER into TRAP for this chart
+# Also keep the OK_MARKERs, so the "sum to 100%" is accurate
+probability <- all_data |>
+  group_by(base_name, variant, benchmark) |>
+  mutate(frac = faults / sum(faults, na.rm = TRUE)) |>
+  ungroup()
+
+# Don't print alphabetically
+probability$resulttype <- factor(probability$resulttype, levels = marker_order)
+probability$variant <- factor(
+  probability$variant,
+  levels = c("c", "aot", "interp")
+)
+
+plot <- ggplot(
+  probability,
+  aes(x = variant, y = frac, fill = resulttype)
+) +
+  geom_col() +
+  facet_grid(benchmark ~ base_name) +
+  scale_y_continuous(labels = scales::percent) +
+  labs(
+    title = "Fault Probability per Fault Space",
+    x = NULL,
+    y = "Probability of Failure",
+    fill = "Fault Type"
+  ) +
+  theme_minimal() +
+  theme(
+    plot.title = element_text(size = 13, face = "bold"),
+    axis.text.x = element_text(angle = 45, hjust = 1)
+  )
+
+out_suffix <- gsub("^resultsdata|\\.csv$", "", csv_suffix)
+filename <- paste0("injections/fault_probability", out_suffix, ".svg")
+ggsave(filename, plot = plot, width = 13, height = 8)