mirror of
https://github.com/Druthulu/BFM-decomp
synced 2026-09-26 13:33:34 -04:00
Drew T
e5a2bd4083
- onboarded ov_{SC01_000,SC01_001,SC02_000,SC02_003,SC03_002,SC03_006,
SC04_000,SC04_018,SC04_019,SC05_000,SC06_000,SC07_000} via tools/new_overlay.sh
— spans all 7 SC areas + 2 full duplicate pairs (SC02_000≡003, SC04_018≡019)
- each byte-identical at 100% INCLUDE_ASM (non-4-aligned auto-handled); no
position-lock anomalies — the cross-shape risk is retired before the full onboard
- make check-all = 18/18 passed (main + resident + 4 prior + 12 new)
- config/overlays.mk + 4 report dicts auto-registered (sentinel, idempotent)
- ghidra/ DB churn NOT staged (R23); asm/build/assets/.run gitignored
148 lines
8.0 KiB
Python
148 lines
8.0 KiB
Python
#!/usr/bin/env python3
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"""Difficulty-ranked inventory of UNMATCHED functions — the harvest queue for matching.
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Ghidra-free: parses each unmatched stub's asm/nonmatchings/800/<name>.s for size, control
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flow, jump-table presence, and call count, then ranks easiest-first. Jump-table functions
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score high (they need the deferred rodata-island workflow, Task 2'). Writes the actionable
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easy queue to docs/difficulty.md and the full CSV to .run/difficulty.csv.
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Usage: tools/difficulty.py [TOP] [--binary <alias>] (TOP default 120; binary default main)
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"""
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import re, sys, pathlib
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ROOT = pathlib.Path(__file__).resolve().parent.parent
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# Per-binary config (Phase 9). main = the retail EXE (current paths = no-op default).
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# The overlay src/asm subtree LAYOUT is a Phase-10 decision (main = the originals).
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BINARIES = {
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"main": dict(src="src", asm="asm/nonmatchings", md="docs/difficulty.md", csv=".run/difficulty.csv"),
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"resident": dict(src="src/resident", asm="asm/resident/nonmatchings",
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md="docs/difficulty.resident.md", csv=".run/difficulty.resident.csv"),
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"ov_SC01_077": dict(src="src/ov_SC01_077", asm="asm/ov_SC01_077/nonmatchings",
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md="docs/difficulty.ov_SC01_077.md", csv=".run/difficulty.ov_SC01_077.csv"),
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"ov_SC01_005": dict(src="src/ov_SC01_005", asm="asm/ov_SC01_005/nonmatchings",
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md="docs/difficulty.ov_SC01_005.md", csv=".run/difficulty.ov_SC01_005.csv"),
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"ov_SC01_006": dict(src="src/ov_SC01_006", asm="asm/ov_SC01_006/nonmatchings",
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md="docs/difficulty.ov_SC01_006.md", csv=".run/difficulty.ov_SC01_006.csv"),
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"ov_SC03_001": dict(src="src/ov_SC03_001", asm="asm/ov_SC03_001/nonmatchings",
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md="docs/difficulty.ov_SC03_001.md", csv=".run/difficulty.ov_SC03_001.csv"),
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"ov_SC01_000": dict(src="src/ov_SC01_000", asm="asm/ov_SC01_000/nonmatchings",
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md="docs/difficulty.ov_SC01_000.md", csv=".run/difficulty.ov_SC01_000.csv"),
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"ov_SC01_001": dict(src="src/ov_SC01_001", asm="asm/ov_SC01_001/nonmatchings",
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md="docs/difficulty.ov_SC01_001.md", csv=".run/difficulty.ov_SC01_001.csv"),
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"ov_SC02_000": dict(src="src/ov_SC02_000", asm="asm/ov_SC02_000/nonmatchings",
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md="docs/difficulty.ov_SC02_000.md", csv=".run/difficulty.ov_SC02_000.csv"),
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"ov_SC02_003": dict(src="src/ov_SC02_003", asm="asm/ov_SC02_003/nonmatchings",
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md="docs/difficulty.ov_SC02_003.md", csv=".run/difficulty.ov_SC02_003.csv"),
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"ov_SC03_002": dict(src="src/ov_SC03_002", asm="asm/ov_SC03_002/nonmatchings",
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md="docs/difficulty.ov_SC03_002.md", csv=".run/difficulty.ov_SC03_002.csv"),
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"ov_SC03_006": dict(src="src/ov_SC03_006", asm="asm/ov_SC03_006/nonmatchings",
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md="docs/difficulty.ov_SC03_006.md", csv=".run/difficulty.ov_SC03_006.csv"),
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"ov_SC04_000": dict(src="src/ov_SC04_000", asm="asm/ov_SC04_000/nonmatchings",
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md="docs/difficulty.ov_SC04_000.md", csv=".run/difficulty.ov_SC04_000.csv"),
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"ov_SC04_018": dict(src="src/ov_SC04_018", asm="asm/ov_SC04_018/nonmatchings",
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md="docs/difficulty.ov_SC04_018.md", csv=".run/difficulty.ov_SC04_018.csv"),
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"ov_SC04_019": dict(src="src/ov_SC04_019", asm="asm/ov_SC04_019/nonmatchings",
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md="docs/difficulty.ov_SC04_019.md", csv=".run/difficulty.ov_SC04_019.csv"),
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"ov_SC05_000": dict(src="src/ov_SC05_000", asm="asm/ov_SC05_000/nonmatchings",
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md="docs/difficulty.ov_SC05_000.md", csv=".run/difficulty.ov_SC05_000.csv"),
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"ov_SC06_000": dict(src="src/ov_SC06_000", asm="asm/ov_SC06_000/nonmatchings",
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md="docs/difficulty.ov_SC06_000.md", csv=".run/difficulty.ov_SC06_000.csv"),
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"ov_SC07_000": dict(src="src/ov_SC07_000", asm="asm/ov_SC07_000/nonmatchings",
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md="docs/difficulty.ov_SC07_000.md", csv=".run/difficulty.ov_SC07_000.csv"),
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# <<< overlays: tools/new_overlay.sh inserts ov_* entries above this line (Phase 13) >>>
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}
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SRCS = ASM_ROOT = MD = CSV = None # set by main() from --binary
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def find_s(name):
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"""Locate <name>.s in any asm/nonmatchings/<seg>/ subdir."""
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for p in sorted(ASM_ROOT.glob(f"*/{name}.s")):
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return p
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return None
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INSTR = re.compile(r'^\s*/\*\s*[0-9A-Fa-f]+\s+([0-9A-Fa-f]+)\s+[0-9A-Fa-f]+\s*\*/\s+([a-z][a-z0-9.]*)')
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BRANCH = re.compile(r'^b(eq|ne|gez|gtz|lez|ltz|nez|eqz|c1t|c1f|gezal|ltzal)?z?$')
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def is_data_blob(txt):
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return 'glabel' not in txt and 'jlabel' not in txt and 'dlabel' in txt
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def unmatched_stubs():
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"""INCLUDE_ASM names that are real functions (exclude data-blobs) and not inside NON_MATCHING."""
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out = []
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for src in SRCS:
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lines = src.read_text().split('\n'); n = len(lines); i = 0
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while i < n:
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s = lines[i].strip()
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if s.startswith('#ifdef NON_MATCHING'):
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while i < n and not lines[i].strip().startswith('#endif'):
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i += 1
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i += 1; continue
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m = re.match(r'INCLUDE_ASM\("[^"]+",\s*(\w+)\)', s)
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if m:
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out.append(m.group(1))
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i += 1
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return out
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def analyze(name):
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p = find_s(name)
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if p is None: return None
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txt = p.read_text()
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if is_data_blob(txt): return None # not a function
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nins = branches = ncalls = 0; last_vaddr = None; jtbl = False
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if 'jtbl_' in txt: jtbl = True
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for ln in txt.splitlines():
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m = INSTR.match(ln)
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if not m: continue
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nins += 1; last_vaddr = int(m.group(1), 16); mn = m.group(2)
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if mn == 'jal': ncalls += 1
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elif mn == 'j': branches += 1
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elif mn == 'jr' and '$ra' not in ln: jtbl = True # indirect jump = switch/jumptable
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elif BRANCH.match(mn): branches += 1
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score = nins + 3*branches + 25*(1 if jtbl else 0) + 2*ncalls
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return dict(name=name, nins=nins, branches=branches, ncalls=ncalls,
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jtbl=jtbl, leaf=(ncalls == 0), score=score)
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def main():
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import argparse
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global SRCS, ASM_ROOT, MD, CSV
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ap = argparse.ArgumentParser(description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter)
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ap.add_argument("top", nargs="?", type=int, default=120)
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ap.add_argument("--binary", default="main", choices=list(BINARIES))
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a = ap.parse_args()
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cfg = BINARIES[a.binary]
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SRCS = sorted((ROOT / cfg["src"]).glob("*.c"))
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ASM_ROOT = ROOT / cfg["asm"]
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MD = ROOT / cfg["md"]
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CSV = ROOT / cfg["csv"]
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top = a.top
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rows = [r for r in (analyze(n) for n in unmatched_stubs()) if r]
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rows.sort(key=lambda r: (r['score'], r['name']))
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CSV.parent.mkdir(exist_ok=True)
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CSV.write_text("name,score,nins,branches,ncalls,jtbl,leaf\n" +
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"".join(f"{r['name']},{r['score']},{r['nins']},{r['branches']},"
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f"{r['ncalls']},{int(r['jtbl'])},{int(r['leaf'])}\n" for r in rows))
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trivial = sum(1 for r in rows if r['nins'] <= 5)
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leaves = sum(1 for r in rows if r['leaf'] and not r['jtbl'])
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jtbls = sum(1 for r in rows if r['jtbl'])
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md = ["# Unmatched difficulty inventory (generated by tools/difficulty.py — harvest queue)",
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"",
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f"unmatched functions : {len(rows)}",
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f"trivial (<=5 ins) : {trivial}",
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f"non-jtbl leaves : {leaves} (best harvest targets)",
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f"jump-table funcs : {jtbls} (deferred — need the rodata-island workflow, Task 2')",
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"",
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f"## Easiest {min(top, len(rows))} unmatched (score asc) — the work queue",
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"| score | name | nins | br | calls | jtbl | leaf |",
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"|---|---|---|---|---|---|---|"]
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for r in rows[:top]:
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md.append(f"| {r['score']} | {r['name']} | {r['nins']} | {r['branches']} | "
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f"{r['ncalls']} | {'Y' if r['jtbl'] else '-'} | {'Y' if r['leaf'] else '-'} |")
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MD.write_text("\n".join(md) + "\n")
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print("\n".join(md[:9]))
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print(f"... full table -> {MD.relative_to(ROOT)} (top {top}), CSV -> {CSV.relative_to(ROOT)}")
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if __name__ == "__main__":
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main()
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