arcattackandClaude Opus 4.8
f914fc040a
Full migration of the 2236-line monolithic CLAUDE.md into the progressive-context knowledge graph (per spark-lesson / expert-seed.md), so the deep RE knowledge loads on-demand instead of every session. ZERO CONTEXT LOST: - docs/PROGRESS_LOG.md = the complete old CLAUDE.md, VERBATIM (byte-identical) -- the lossless safety net + the "full detail" quick-lookup fallback. - 18 context/*.md topic files (1343 lines) digest every section (§1-3 -> project-overview, §4 -> content-archives, §5 -> asset-formats/bgf-format, §5a -> source-completeness, §5b/§8 -> wintesla-port, §7/§10 -> locomotion, §10a -> build-and-run, §10b -> reconstruction-method, §10c -> combat-damage + reconstruction-gotchas, §10d -> subsystems, render notes -> rendering, gauges -> gauges-hud, MP -> multiplayer, §9 -> open-questions). - reference/glossary.yaml (53 terms). decomp-reference.md = the offsets/ClassIDs/addresses hub. CLAUDE.md (160 lines) = router: identity, answer/reason protocols, quick-lookup table, evidence tiers (T0 engine-truth / T1 decompiled+verified / T2 reconstructed+runtime / T3 guarded / T4 hypothesis), conventions + DO-NOT (the systemic bug classes), structure. Retains the load-bearing work directives (build recipe pointer, "keep current" mandate). Knowledge graph validates CLEAN (scratchpad/checkctx.py -- all [[links]] + quick-lookup + docs refs resolve; [[name]] -> topic file or glossary term). docs/*.md ledgers stay as the detailed logs; context/*.md are the curated digests that route into them. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
57 lines
3.5 KiB
Markdown
57 lines
3.5 KiB
Markdown
---
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id: reconstruction-method
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title: "Reconstruction Method — the loop, the no-stand-ins rule, decomp technique"
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status: established
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source_sections: "PROGRESS_LOG.md §10b, §5a (decompilation), §10c"
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related_topics: [reconstruction-gotchas, decomp-reference, source-completeness]
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key_terms: [decomp, oracle, bridge, BTL4OPT, WinTesla]
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---
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# Reconstruction Method
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How the missing BT game logic is rebuilt from the binary. The governing rule: **no stand-ins.**
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Full detail: `docs/PROGRESS_LOG.md §10b`; the systemic bug classes are [[reconstruction-gotchas]].
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## The loop (per feature)
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1. Read the RAW decomp `reference/decomp/all/part_*.c` for the relevant `FUN_xxxx`.
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2. Map `FUN_`/`DAT_`/`this+0xNN` to engine symbols using: the BT headers + the WinTesla MUNGA
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source + `game/reconstructed/CLASSMAP.md` + **RP's parallel code** (VTV≈mech, WEAPSYS≈weapons).
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3. Write the **real** reconstruction into `game/reconstructed/*.cpp`.
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4. Build; run env-gated; read `btl4.log` (grep `[anim]/[drive]/[target]/[fire]/[damage]` markers).
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5. cdb on any crash. `static_assert`-lock the layout against the binary's offsets. [T2]
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## RULE: no stand-ins
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The full game logic IS in the pseudocode (the binary ran the game); a "gap" is a reconstruction
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stub not yet filled, not a hole in the original. **Never write stand-in/placeholder logic for an
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apparent gap — read the decomp.** (User: "there are no gaps, just work to be done.") Bring-up
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scaffolding (env-var paths, explosion-for-beam, a player-gated drive) is clearly MARKED and meant
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to be REPLACED by the real reconstructed system, never to substitute for reading the decomp. [T2]
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## Decompilation stack (Plan B — in progress)
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- **Ghidra 12.1.2 + JDK21** installed under `tools/` (portable). `ExportBTSource.java` run headless
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on `BTL4OPT.EXE` → real decompiled C in `reference/decomp/recovered/`. The pass is
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**assert-anchored** (few funcs/file — anchored on the asserts that carry source paths). [T2]
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- For a `FUN_` the assert-anchored exporter skipped: **`tools/disas2.py <VA> [len]`** (capstone
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disassembly of `BTL4OPT.EXE` — recovers x87 math Ghidra drops, folds known calls + float
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constants). Or `DecompVSS.java` (headless address-list decompiler). [T2]
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- **Resolving a `.data` fn-pointer** (a `PTR_LAB_xxxx` callback/vtable slot the decomp didn't
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export): PE-parse the DWORD at its VA, then capstone-disassemble the target. Used for the gait
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callbacks (`@0x4a6d8c`), the valve handler (`@0x4ae464`), gauge widget slots. [T2]
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- **`.data` float constants** are the biggest "couldn't recover" bucket (tuning values); read them
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as the x87 80-bit `float10` the decomp uses, not 32-bit float (`scratchpad/rdtbyte.py`). [T2]
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## Effort model (honest)
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~0.5-1.5 hr/module → ~30-50 agent-hours + human review for ~40 modules, with a long tail (modules
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with no surviving `.HPP` fragment, or split across decomp windows, cost more). Process upgrades:
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per-class function lists (not address clusters), complete vtable rows, recover `.data` constants. [T3]
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## Workflows (for scale)
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For exhaustive multi-function decomp analysis, fan out a **read-only Workflow** (understanding
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phase — one agent per function/class produces an offset map + findings, + an adversarial verify),
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THEN implement hands-on so each change is visible + consistent. This is the §10c pattern; used for
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the ground-model decode (10 agents), the alarm-unification (8), the gauge-widget decode (6). [T2]
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## Key Relationships
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- Bug classes: [[reconstruction-gotchas]] (check FIRST). Reference data: [[decomp-reference]].
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- Why it's needed: [[source-completeness]].
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