// coverage.jsx — Tab: Pattern Coverage // Reviewers (Y) × 9 categories (X). // // Cell fill comes from two sources, merged: // 1. category_freq on reviewer fingerprints (0-100 score from Phase 2 synthesis) // — reliable signal for ALL reviewers regardless of pattern selection. // 2. Evidence quotes from DATA.patterns — populates the click-through drawer. // // Using only patterns caused empty rows for reviewers whose patterns weren't // selected in the top-20 (e.g. Spock reviewed 40 PRs but had low-count signals). function buildCoverage() { const cats = DATA.CATEGORIES; const revs = DATA.reviewers.map(r => r.login); // Index reviewer fingerprints by login for O(1) lookup const freqIndex = {}; DATA.reviewers.forEach(r => { freqIndex[r.login] = r.category_freq || {}; }); // Build evidence items from patterns (for drawer) const evidenceIndex = {}; // reviewer → category → [{...}] revs.forEach(r => { evidenceIndex[r] = {}; cats.forEach(c => { evidenceIndex[r][c] = []; }); }); DATA.patterns.forEach(p => { if (!evidenceIndex[p.reviewer] || !evidenceIndex[p.reviewer][p.category]) return; const ev = p.evidence || []; ev.forEach(e => evidenceIndex[p.reviewer][p.category].push( { ...e, signal: p.signal, category: p.category, citation: p.standard_citation } )); }); // Merge: cell value is category_freq score (0-100); items come from pattern evidence const m = {}; revs.forEach(r => { m[r] = {}; cats.forEach(c => { const freq = freqIndex[r]?.[c] ?? 0; m[r][c] = { freq, items: evidenceIndex[r]?.[c] ?? [] }; }); }); return { m, revs, cats }; } // Map category_freq (0-100) → discrete shade level. // Matches the original 4-level palette but driven by synthesis score. function freqToLevel(freq) { if (freq <= 0) return 0; if (freq < 30) return 1; if (freq < 60) return 2; return 3; } // Discrete coverage shades — not a continuous heat map. function coverageStep(freq) { const level = freqToLevel(freq); if (level === 0) return { fill: "var(--bg)", border: "var(--border)", on: false, level: 0 }; if (level === 1) return { fill: "rgba(43,80,232,0.12)", border: "rgba(43,80,232,0.22)", on: true, level: 1 }; if (level === 2) return { fill: "rgba(43,80,232,0.30)", border: "rgba(43,80,232,0.34)", on: true, level: 2 }; return { fill: "rgba(43,80,232,0.55)", border: "rgba(43,80,232,0.50)", on: true, level: 3 }; } function CoverageCell({ data, label, onClick }) { const [hover, setHover] = useState(false); const step = coverageStep(data.freq); const hasEvidence = data.items && data.items.length > 0; // All active cells are clickable — drawer shows quotes if available, // otherwise shows the reviewer's fingerprint focus areas for this category. const clickable = step.on; return ( ); } function CoverageDrawer({ payload, onClose }) { useEffect(() => { const onKey = (e) => { if (e.key === "Escape") onClose(); }; window.addEventListener("keydown", onKey); return () => window.removeEventListener("keydown", onKey); }, [onClose]); if (!payload) return null; const { reviewer, category, cell } = payload; const grp = groupForCategory(category); // Find this reviewer's fingerprint focus areas relevant to this category const reviewerData = DATA.reviewers.find(r => r.login === reviewer); const catKeywords = { grain: ["grain","dedup","fan-out","fanout","partition"], naming: ["naming","convention","snake","prefix"], testing: ["test","fixture","uniqueness","not_null","primary key"], documentation: ["documentation","docs","description","readme","runbook"], style: ["style","cte","qualify","readability","formatting"], performance: ["performance","cost","scan","partition","cluster"], modeling: ["incremental","microbatch","materialization","model layer","staging","mart","scd","exposure"], schema: ["source freshness","schema change","breaking change","exposure","freshness"], "business-logic": ["spec","business logic","gtfs","derived field","conditional"], }; const relevantFocus = reviewerData?.primary_focus_areas?.filter(f => (catKeywords[category] || []).some(kw => f.area.toLowerCase().includes(kw)) ) || []; return (
); } function CoverageTab() { const { m, revs, cats } = useMemo(buildCoverage, []); const [sel, setSel] = useState(null); const labelW = 132; return (

Pattern Coverage

Which review dimensions each reviewer actually covers. Deeper cobalt = reviewed more often. Click a cell to read the evidence.

{/* legend */}
none
{[0, 1, 2, 3].map((n) => (
))}
reviewed
{/* header row of category labels */}
{cats.map(c => (
{c}
))}
{/* one row per reviewer */} {revs.map(r => (
{r}
{cats.map(c => { const cell = m[r][c]; return ( setSel({ reviewer: r, category: c, cell })} /> ); })}
))}
setSel(null)} />
); } window.CoverageTab = CoverageTab;