6fc082ca55
The correlation route is gated on marked-fighter kills, which the pilot manages at about two per five minutes. ob_read.py already reads the counter off the screen, so ob_by_hud.py matches the displayed value against memory directly and needs no kills at all: screenshot, read the digits, keep heap words equal to that value, intersect across readings. Four readings at value 4 narrowed 6156 candidates to 4312, the expected slow drift. Then the HUD read 11 and the intersection collapsed to zero. A word holding this counter must equal 4 at the first four samples and 11 at the last, and none does, so within the entity heap read as big-endian u32 the counter does not exist. It may be u16, u8, little-endian, or outside that region. Both previous hunts assumed big-endian u32 there, so this eliminates the assumption rather than merely failing to find anything. The displayed value also went up, from 4 to 11 over about 340 seconds. A pure countdown of remaining marked targets should not rise, and the deployment work says phase 1 gains no new participants. Three readings are possible and none is tested: the cell being read is not REMAINING OB, the digits are misread, or the counter genuinely counts something that can increase. The two clean readings scored 0.95 to 0.98 against their templates, but 4 and 11 use only digits that are in the strip, which is exactly the selection effect that would hide a wrong reading -- the template set covers 0 1 2 4 8 only, and most samples came back unreadable. Next is widening the scan to u16 and u8 and to little-endian, and beyond the entity heap, which is a change to one function and costs no combat. Extending ob_digits.png with the missing digits would also raise the sample yield, since only two of eleven readings in a 480 s run were usable.
218 lines
9.2 KiB
Markdown
218 lines
9.2 KiB
Markdown
# Hunting REMAINING OB by correlation — method works, run did not finish
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Status: ✅ the correlation method is sound and demonstrated; 🔴 the hunt is
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**unfinished**; 🔴 two self-inflicted defects, one a repeat.
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## The method
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[mission-phase-objectives.md](mission-phase-objectives.md) settles what the
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counter is: Stage 02 phase 1 asks to *"shoot down all invading enemy fighters"*
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and the hints say red **[OB]** markers indicate the targets. So `REMAINING OB`
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must fall when a marked fighter dies — and the per-record craft strength already
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says exactly when that happens, for a *named* unit.
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So instead of scanning for a value, intersect: keep every word in the 32 MB heap
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that fell by the same amount, in the same interval, as an `e010` loss. Each kill
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event should cut the survivor set hard.
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`tools/re-capture/ob_probe2.py`.
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## ✅ It works — one event cut 8 million words to 1056
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```
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t= 219s e010 losses=2 (all=4) words falling by 2: 1056 -> candidates 1056
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```
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From ~8 M candidate words to **1056** on a single event. Two or three more should
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leave a handful.
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## 🔴 The run did not finish, and the candidates were lost
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The turn's timeout fired at t = 219 s, and the probe saved its candidate set
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**only at the end** — so the 1056 were discarded. The follow-up attach then
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started from nothing.
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**This is the same mistake already recorded in
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[guest-stalls.md](guest-stalls.md)**: "the first attempt deferred all analysis to
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the end of the run, and the turn's timeout killed it with 240 s of collected data
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still in memory and nothing written." I wrote that lesson down and then repeated
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it in a new script four iterations later.
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Fixed: candidates are now written to `/tmp/ob_candidates.json` **after every
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event**, and `SYLPH_OB_RESUME=1` loads them so a chained attach keeps
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intersecting on the same mission.
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## 🔴 The attach could not tell a quiet mission from a frozen one
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The follow-up attach logged **535 s with zero losses of any kind**. That is
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exactly what a freeze looks like, and `ob_probe2` had no stall witness, so the
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run cannot say which it was. Also fixed — the witness from `wave7_probe` is now
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carried here.
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Two defects in one iteration, both of them things this corpus had already
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learned. The pattern is that each new probe starts from scratch and re-earns the
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same lessons; the fix that would actually stick is a shared probe harness rather
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than a family of one-off scripts.
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## What is still open
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The hunt itself. The method is demonstrated but no address is identified. What it
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needs is a run that catches **two or three** `e010` kill events, which is the same
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combat-effectiveness limit recorded in
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[mission-objectives-text.md](mission-objectives-text.md) — the preference knob
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gets about two marked-fighter kills per five minutes against a dozen turrets.
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---
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# Second attempt: saving works, the filter was wrong (2026-08-24)
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## ✅ Incremental saving works
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A fresh mission caught one `e010` event at t = 241 s and **wrote 1187 candidates
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to disk immediately**. The turn timeout then fired, exactly as before — but this
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time the data survived it. The fix from the previous iteration is verified.
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The session also now clears `/tmp/ob_candidates.json` at launch: candidate
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*offsets* are only meaningful within one emulator instance, so resuming across
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launches would intersect unrelated addresses.
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## 🔴 The correlation had no value filter, and the survivors were floats
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The 1187 survivors are not counters:
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```
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va 0xbd0a42b8 value 1044450858 (~0.1f)
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va 0xbd140bc0 value 3200164558 (a negative float)
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va 0xbd14a120 value 3212461993
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```
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The filter matched on the **delta** alone, so any two float bit patterns whose
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integer representations differ by exactly `lost` qualified. In a 32 MB heap full
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of positions and velocities that is thousands of words.
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Fixed: candidates must also *look like a counter* — a small non-negative integer
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(`0 ≤ v < 1000`) in both samples. That removes float noise by construction rather
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than hoping the intersection washes it out.
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## 🔴 The attach was frozen, and the witness said so
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The follow-up attach logged **0 events across 520 s**, which reads like the
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combat-effectiveness limit again. It was not: **25 of its 26 samples were flagged
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`GUEST STALLED`**. The guest was frozen for essentially the whole window.
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The witness added last iteration did its job. The lesson is about reading it —
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the run summary quoted "0 events" first and the stall count only turned up on a
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deliberate check. **A run's witness result should be the first thing looked at,
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before any interpretation of what the run "showed".**
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## Still unfinished
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No address identified. What is needed is unchanged — two or three `e010` kill
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events in *non-stalled* samples — and the two obstacles are now clearly separate:
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the freeze rate, and the pilot managing roughly two marked-fighter kills per five
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minutes.
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---
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# ✅ The method narrows hard — and refutes turret tracking (2026-08-24)
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With the value filter in place, an attach watching **turret** losses (which are
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frequent, unlike marked-fighter kills):
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```
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t= 45s e007 losses=2 words falling by 2: 374 -> candidates 374
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t=134s e007 losses=4 words falling by 4: 1001 -> candidates 2
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t=156s e007 losses=2 words falling by 2: 526 -> candidates 0
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```
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**374 → 2 → 0.** That is exactly the behaviour a correlation search should show,
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and it ends in a refutation rather than fizzling out:
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> **No plain `u32` in `0xBD000000–0xBE000000` decrements consistently with turret
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> kills.**
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Witness first, as the rule now says: 12 of 25 samples stalled, but **all four kill
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events fall in the early non-stalled stretch** (t = 45–177 s), so the events
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themselves are sound.
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## 🟡 The negative fits the objective text
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This is what the objective text predicts. Stage 02 phase 1 asks to *"shoot down
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all invading enemy **fighters**"*, and turrets are not fighters — so a counter of
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remaining marked targets **should not** move when a turret dies. The refutation is
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evidence *for* the reading in
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[mission-phase-objectives.md](mission-phase-objectives.md), not against it.
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It also rules out the cheaper alternative reading, that `REMAINING OB` is a
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general kill or enemy-remaining tally. It is not: it ignored ten turret deaths.
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## What this leaves
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The method is proven and the search region is right — `0xbdb59668`, where the
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counter was originally seen, is inside the scanned range. What is missing is
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still **two or three `e010` kill events in non-stalled samples**, and the same
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two obstacles: the freeze rate, and the pilot's ~2 marked-fighter kills per five
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minutes.
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One clean 220 s run this iteration produced **zero** `e010` kills, which is the
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limit stated plainly.
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---
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# ✅ A kill-free route via the HUD — and it refutes the u32 assumption (2026-08-24)
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The correlation route is gated on marked-fighter kills, which the pilot gets at
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about two per five minutes. But `ob_read.py` already reads the counter off the
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screen, so the value can be matched against memory directly — no kills needed.
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`tools/re-capture/ob_by_hud.py`: screenshot → read the digits → keep heap words
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equal to that value → intersect across readings.
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```
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t= 7s HUD=4 words==4: 6156 -> candidates 6156
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t= 42s HUD=4 words==4: 6256 -> candidates 5153
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t= 75s HUD=4 words==4: 6327 -> candidates 4620
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t=108s HUD=4 words==4: 6451 -> candidates 4312
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t=142s .. t=312s HUD unreadable ('00?', '??1', '???')
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t=347s HUD=11 words==11: 1052 -> candidates 0
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```
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## 🔴 Refuted: the counter is not a plain big-endian u32 in the entity heap
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Four readings at value 4 narrowed 6156 → 4312 — the expected slow drift. Then the
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HUD read **11**, and the intersection collapsed to **zero**.
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A word that genuinely holds this counter must equal 4 at the first four samples
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*and* 11 at the last. None does. So within `0xBD000000–0xBE000000`, read as
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big-endian `u32`, **the counter does not exist**. It may be `u16`, `u8`,
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little-endian, or simply outside that region.
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That is worth having: both hunts so far assumed BE-`u32` in the entity heap, and
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that assumption is now eliminated rather than merely unproductive.
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## 🟡 The displayed value went UP, 4 → 11
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Over ~340 s the counter *increased*. A pure countdown of remaining marked targets
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should not do that — unless targets were added, which the deployment work says
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does not happen for phase 1
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([mission-phase-deployment.md](mission-phase-deployment.md)).
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Possible readings, none tested: the cell being read is not `REMAINING OB`; the
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digits are misread (the template strip only covers **0 1 2 4 8**, so 3/5/6/7/9
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come back as `?` — the many unreadable samples above); or the counter genuinely
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counts something that can rise.
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The two clean readings scored 0.95–0.98 against their templates, so a misread of
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those specific frames is unlikely — but "4" and "11" use only digits that *are*
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in the strip, which is exactly the selection effect that would hide a wrong
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reading.
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## Next
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Widen the encoding: search `u16` and `u8`, little-endian as well as big, and
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beyond the entity heap. That is a change to one scan function, and unlike the
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kill-driven route it costs no combat.
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Also worth extending `ob_digits.png` with the missing digits — most samples were
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unreadable, which is why only two data points survived a 480 s run.
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