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8c10cf2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 | #!/usr/bin/env python3
"""Summarize per-model success rate for LandingPageGenerator-H_A2A.
Success criterion: `file_exists` in `html_validation.json` is true.
"""
import json
import os
from pathlib import Path
from collections import defaultdict
# Base directory and model list
BASE_DIR = Path("/Users/wzr/TOSEM-2025/RESULTS")
MODELS = [
"DeepSeek-R1",
"DeepSeek-V3-1",
"GPT-4o-mini",
"GPT-5",
"Gemini-2.5-flash",
"Gemini-2.5-flash-nothinking",
"Qwen3-235b",
]
PROJECT_NAME = "LandingPageGenerator-H_A2A"
def analyze_model_results():
"""Analyze execution results for each model."""
results = {}
for model in MODELS:
test_results_dir = BASE_DIR / model / PROJECT_NAME / "test_results"
if not test_results_dir.exists():
print(
f"⚠️ test_results directory not found for model {model}: {test_results_dir}"
)
continue
model_stats = {
"success_count": 0,
"failure_count": 0,
"total_count": 0,
"sessions": [],
}
# Iterate over all session subfolders
for session_dir in sorted(test_results_dir.iterdir()):
if not session_dir.is_dir():
continue
html_validation = session_dir / "html_validation.json"
if not html_validation.exists():
continue
try:
with open(html_validation, "r", encoding="utf-8") as f:
validation_data = json.load(f)
# Success criterion: file_exists is true
success = validation_data.get("file_exists", False)
score = validation_data.get("score", 0)
grade = validation_data.get("grade", "F")
model_stats["total_count"] += 1
if success:
model_stats["success_count"] += 1
else:
model_stats["failure_count"] += 1
model_stats["sessions"].append(
{
"session": session_dir.name,
"success": success,
"file_exists": success,
"score": score,
"grade": grade,
"error": validation_data.get("error_message"),
}
)
except Exception as e:
print(f"❌ Error reading {html_validation}: {e}")
results[model] = model_stats
return results
def print_summary(results):
"""Print a summary to stdout."""
print("\n" + "=" * 80)
print(f"Model Execution Summary - {PROJECT_NAME}")
print("=" * 80 + "\n")
for model, stats in results.items():
total = stats["total_count"]
success = stats["success_count"]
failure = stats["failure_count"]
if total > 0:
success_rate = (success / total) * 100
print(f"📊 {model}")
print(f" Total: {total}")
print(f" Success: {success} (file_exists=true, {success_rate:.1f}%)")
print(f" Failure: {failure} (file_exists=false, {100-success_rate:.1f}%)")
print()
else:
print(f"📊 {model}")
print(" No data")
print()
print("=" * 80)
def save_detailed_results(results, output_file="success_detailed_results.json"):
"""Save detailed results to a JSON file."""
output_path = Path(__file__).parent / output_file
with open(output_path, "w", encoding="utf-8") as f:
json.dump(results, f, indent=2, ensure_ascii=False)
print(f"\n✅ Detailed results saved to: {output_path}")
def save_csv_summary(results, output_file="success_rate.csv"):
"""Save the summary to a CSV file."""
import csv
output_path = Path(__file__).parent / output_file
with open(output_path, "w", newline="", encoding="utf-8") as f:
writer = csv.writer(f)
writer.writerow(["Model", "Total", "Success", "Failure", "Success_Rate(%)"])
for model, stats in results.items():
total = stats["total_count"]
success = stats["success_count"]
failure = stats["failure_count"]
success_rate = (success / total * 100) if total > 0 else 0
writer.writerow([model, total, success, failure, f"{success_rate:.2f}"])
print(f"✅ CSV summary saved to: {output_path}")
if __name__ == "__main__":
print(f"Starting success rate analysis - {PROJECT_NAME}")
print("Success criterion: file_exists in html_validation.json is true\n")
results = analyze_model_results()
print_summary(results)
save_detailed_results(results)
save_csv_summary(results)
print("\n✅ Done!")
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