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Body normalisation: per-method similarity score + leaf delta

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Turns the dispatch axis from a binary changed/unchanged into a "how much" measure
of code change — the original goal. ams.normalize compares two body fingerprints
(the ordered leaf-call anchors) with difflib after collapsing consecutive-duplicate
anchors (a load-twice codegen artefact), yielding a 0-100 similarity and the exact
leaves that appeared/vanished.

Every dispatch `changed` entry now carries body={similarity, added, removed}, and the
block carries a summary={shared, identical, changed, mean_similarity}.

Golden pair (cross-compiler): 470 shared bodies, 131 identical, mean 66% similar;
Animo SHOW/HIDE/PAUSE/RESUME come out 100% despite MSVC6 vs MSVC8, LOAD 50% with the
swapped leaves spelled out.

- normalize.py: canonical / body_similarity / body_delta
- diff: _dispatch_diff enriches changed with body + adds summary
- render: METHOD BODIES shows %, leaf delta, summary line
- UI: similarity % + leaf delta + axis summary
- tests: 5 new -> 34/34

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
This commit is contained in:
Patryk Gensch
2026-05-31 13:23:15 +02:00
parent 27399a52b1
commit b0d3d22445
7 changed files with 198 additions and 18 deletions
Download Patch File Download Diff File Expand all files Collapse all files

28
ams/api/static/app.js
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@@ -240,18 +240,34 @@ function axisCard(ax, block) {
const sortByName = (arr) => arr.slice().sort((x, y) => ax.name(x).localeCompare(ax.name(y)));
for (const it of sortByName(block.added)) body.append(el("div", { class: "row r-add" }, ax.fmt(it)));
for (const it of sortByName(block.removed)) body.append(el("div", { class: "row r-del" }, ax.fmt(it)));
const leaves = (arr) => "[" + arr.slice(0, 4).join(", ") + (arr.length > 4 ? "…+" + (arr.length - 4) : "") + "]";
for (const ch of block.changed.slice().sort((x, y) => ax.name(x.item).localeCompare(ax.name(y.item)))) {
const deltas = Object.entries(ch.changes).map(([f, v]) =>
(Array.isArray(v[0]) || Array.isArray(v[1]))
? `${f}: ${(v[0] || []).length} → ${(v[1] || []).length}`
: `${f}: ${v[0]} → ${v[1]}`).join(", ");
body.append(el("div", { class: "row r-chg" }, ax.name(ch.item), " ", el("span", { class: "delta" }, deltas)));
let deltas, sim = null;
if (ch.body) { // method-body diff: similarity score + leaf-level delta
sim = ch.body.similarity;
const parts = [];
if (ch.body.added && ch.body.added.length) parts.push("+" + leaves(ch.body.added));
if (ch.body.removed && ch.body.removed.length) parts.push("−" + leaves(ch.body.removed));
deltas = parts.join(" ") || (ch.changes.impl ? `impl ${ch.changes.impl[0]} → ${ch.changes.impl[1]}` : "");
} else {
deltas = Object.entries(ch.changes).map(([f, v]) =>
(Array.isArray(v[0]) || Array.isArray(v[1]))
? `${f}: ${(v[0] || []).length} → ${(v[1] || []).length}`
: `${f}: ${v[0]} → ${v[1]}`).join(", ");
}
const row = el("div", { class: "row r-chg" }, ax.name(ch.item), " ");
if (sim != null) row.append(el("span", { class: "simpct" }, sim + "%"), " ");
row.append(el("span", { class: "delta" }, deltas));
body.append(row);
}
const sum = block.summary
? el("span", { class: "axsum" }, `śr. ${block.summary.mean_similarity}% · ${block.summary.changed}/${block.summary.shared} zmienionych`)
: null;
return el("details", { class: "axis", open: true },
el("summary", {}, el("span", { class: "title" }, ax.title),
badge("b-add", "+", block.added.length),
badge("b-del", "−", block.removed.length),
badge("b-chg", "~", block.changed.length)),
badge("b-chg", "~", block.changed.length), sum),
body);
}