alpaylan · March 25, 2026 19:38
diff --git a/report.html b/report.html
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 </head>
 <body>

 <div class="header">
  <h1>ETNA Report: <span id="exp-name"></span></h1>
  <div class="meta">Generated <span id="gen-time"></span> &middot; <span id="metric-count"></span> records</div>
 </div>

 <div class="nav" id="nav">
  <button data-view="overview" class="active">Overview</button>
  <button data-view="buckets">Bucket Charts</button>
  <button data-view="strategies">Strategy Comparison</button>
  <button data-view="mutations">Mutation Matrix</button>
  <button data-view="drilldown">Drill-Down</button>
  <button data-view="rawdata">Raw Data</button>
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  <!-- OVERVIEW -->
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    <div class="cards" id="overview-cards"></div>
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      <span class="section-title" style="margin-bottom:0">Summary by Workload / Property / Mutation</span>
      <label style="margin-left:auto;">Aggregation:</label>
      <div class="toggle-group" id="overview-agg-toggle">
        <button class="active" data-mode="mean">Mean</button>
        <button data-mode="median">Median</button>
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    </div>
    <div class="table-wrap">
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          <th data-col="workload">Workload <span class="sort-arrow">&#9650;</span></th>
          <th data-col="property">Property <span class="sort-arrow">&#9650;</span></th>
          <th data-col="mutation">Mutation <span class="sort-arrow">&#9650;</span></th>
          <th data-col="strategies">Strategies <span class="sort-arrow">&#9650;</span></th>
          <th data-col="trials">Trials <span class="sort-arrow">&#9650;</span></th>
          <th data-col="bugRate">Bug Rate <span class="sort-arrow">&#9650;</span></th>
          <th data-col="aggTime" id="overview-th-time">Mean TTF <span class="sort-arrow">&#9650;</span></th>
          <th data-col="aggTests" id="overview-th-tests">Mean ITF <span class="sort-arrow">&#9650;</span></th>
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        <tbody></tbody>
      </table>
    </div>
  </div>

  <!-- BUCKET CHARTS -->
  <div class="view" id="view-buckets">
    <div class="controls">
      <label>Metric:</label>
      <select id="bucket-metric">
        <option value="time">Time to Failure</option>
        <option value="tests">Inputs to Failure</option>
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      <label>Aggregation:</label>
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        <button class="active" data-mode="mean">Mean</button>
        <button data-mode="median">Median</button>
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      <button class="btn" id="bucket-apply">Apply</button>
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      <label><input type="checkbox" class="bucket-groupby-cb" value="workload" checked> Workload</label>
      <label><input type="checkbox" class="bucket-groupby-cb" value="strategy" checked> Strategy</label>
      <label><input type="checkbox" class="bucket-groupby-cb" value="cross"> Cross</label>
      <button class="btn" id="bucket-compare-btn" style="margin-left:auto;">Compare</button>
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  <!-- STRATEGY COMPARISON -->
  <div class="view" id="view-strategies">
    <div class="controls">
      <label>Workload:</label>
      <select id="strat-workload"></select>
      <label>Metric:</label>
      <select id="strat-metric">
        <option value="time">Time</option>
        <option value="tests">Tests</option>
        <option value="shrinking_time">Shrinking Time</option>
        <option value="generation_time">Generation Time</option>
        <option value="execution_time">Execution Time</option>
        <option value="discards">Discards</option>
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      <label>Aggregation:</label>
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        <button class="active" data-mode="mean">Mean</button>
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        <button data-mode="log">Log</button>
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      <h3 id="strat-dist-title">Distribution by Strategy &amp; Property</h3>
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  <!-- MUTATION MATRIX -->
  <div class="view" id="view-mutations">
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      <label>Workload:</label>
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      <label>Property:</label>
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      <label>Mutation:</label>
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      <label>Strategy:</label>
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        <h3>Time per Trial</h3>
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        <h3>Tests per Trial</h3>
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          <th>Time</th>
          <th>Tests</th>
          <th>Discards</th>
          <th>Shrinking</th>
          <th>Generation</th>
          <th>Execution</th>
          <th>Counterexample</th>
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        <tbody></tbody>
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    </div>
  </div>

  <!-- RAW DATA -->
  <div class="view" id="view-rawdata">
    <div class="controls">
      <label>Show:</label>
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        <option value="50">50</option>
        <option value="100" selected>100</option>
        <option value="250">250</option>
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"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";
 const EXPERIMENT_NAME = "rust-strategy-triad";
 const GENERATED_AT = "2026-03-25 19:38 UTC";
 // docs/workloads/*.json — maps workload name to [{mutations, tasks: [{property}]}]
 const WORKLOAD_DOCS = {"bst":[{"mutations":["insert_1"],"tasks":[{"counterexample":"((T E 2 1 E) 0 2 0)","property":"InsertPost"},{"counterexample":"((T E 1 0 E) 0 0)","property":"InsertModel"},{"counterexample":"((T E 1 0 E) 0 0 0)","property":"DeleteInsert"},{"counterexample":"(E 1 0 0 0)","property":"InsertInsert"},{"counterexample":"(E (T E 1 1 E) 0 0)","property":"InsertUnion"},{"counterexample":"((T E 2 0 E) E 0 0)","property":"UnionDeleteInsert"}]},{"mutations":["insert_2"],"tasks":[{"counterexample":"((T E 0 1 E) 1 0 0)","property":"InsertPost"},{"counterexample":"((T E -2 0 E) 0 0)","property":"InsertModel"},{"counterexample":"((T E 0 2 (T E 1 0 E)) 0 0 0)","property":"InsertDelete"},{"counterexample":"((T E 0 0 E) 0 1 0)","property":"DeleteInsert"},{"counterexample":"(E 0 1 0 0)","property":"InsertInsert"},{"counterexample":"(E (T E 0 0 E) 1 0)","property":"InsertUnion"},{"counterexample":"((T E -2 0 E) E 0 0)","property":"UnionDeleteInsert"}]},{"mutations":["insert_3"],"tasks":[{"counterexample":"((T E 3 0 E) 3 3 1)","property":"InsertPost"},{"counterexample":"((T E 0 1 E) 0 0)","property":"InsertModel"},{"counterexample":"((T (T E 0 0 E) 2 0 E) 2 2 0)","property":"InsertDelete"},{"counterexample":"(E 0 0 1 0)","property":"InsertInsert"},{"counterexample":"(E (T E 0 0 E) 1 0)","property":"InsertUnion"},{"counterexample":"((T E -2 2 E) E -2 0)","property":"UnionDeleteInsert"}]},{"mutations":["delete_4"],"tasks":[{"counterexample":"((T E 0 0 E) 1)","property":"DeleteModel"},{"counterexample":"((T E 0 0 E) 1 0)","property":"DeletePost"},{"counterexample":"((T (T (T E 0 0 E) 3 5 E) 5 0 E) 5 3)","property":"DeleteDelete"},{"counterexample":"(E 0 1 0)","property":"DeleteInsert"},{"counterexample":"((T E -1 0 E) (T E 0 1 E) -1)","property":"DeleteUnion"},{"counterexample":"(E 0 1 0)","property":"InsertDelete"},{"counterexample":"((T E 0 1 E) (T E 1 0 E) 0 0)","property":"UnionDeleteInsert"}]},{"mutations":["delete_5"],"tasks":[{"counterexample":"((T (T E 1 0 E) 3 0 E) 1)","property":"DeleteModel"},{"counterexample":"((T (T E 2 0 E) 4 1 E) 2 2)","property":"DeletePost"},{"counterexample":"((T E -4 0 (T E 4 4 E)) 4 -4)","property":"DeleteDelete"},{"counterexample":"((T E 2 0 E) -2 -2 0)","property":"DeleteInsert"},{"counterexample":"((T E -1 0 (T E 0 0 E)) (T E -2 2 E) -1)","property":"DeleteUnion"},{"counterexample":"((T (T E -1 0 E) 0 0 E) E 0 0)","property":"UnionDeleteInsert"}]},{"mutations":["union_6"],"tasks":[{"counterexample":"((T E 0 0 E) (T E 0 0 E))","property":"UnionValid"},{"counterexample":"((T E 0 0 (T E 1 1 E)) (T E 0 0 E) 1)","property":"UnionPost"},{"counterexample":"((T E 0 0 E) (T E 0 0 E))","property":"UnionModel"},{"counterexample":"((T E 2 2 E) (T E -1 0 E) -1)","property":"DeleteUnion"},{"counterexample":"(E (T E 0 0 E) 1 0)","property":"InsertUnion"},{"counterexample":"((T E 0 0 E) (T E 0 0 E) 0 0)","property":"UnionDeleteInsert"},{"counterexample":"((T E 0 1 E) (T E 0 1 E) (T E 0 0 E))","property":"UnionUnionAssoc"}]},{"mutations":["union_7"],"tasks":[{"counterexample":"(E (T E 0 2 (T E 0 0 E)))","property":"UnionValid"},{"counterexample":"((T (T E -2 0 E) 2 0 E) (T E 0 0 E) -2)","property":"UnionPost"},{"counterexample":"((T E -1 0 E) (T (T E -2 1 E) 0 0 E))","property":"UnionModel"},{"counterexample":"((T E 0 0 E) (T (T E 0 0 E) 2 0 E) 2)","property":"DeleteUnion"},{"counterexample":"((T E 0 0 E) (T E 1 1 E) 1 0)","property":"InsertUnion"},{"counterexample":"((T (T E -1 0 E) 0 0 E) E 0 0)","property":"UnionDeleteInsert"},{"counterexample":"((T E 0 0 E) (T E 1 0 E) (T E 1 1 E))","property":"UnionUnionAssoc"}]},{"mutations":["union_8"],"tasks":[{"counterexample":"((T (T E 4 4 E) 2147483647 0 E) (T E 4 0 E) 4)","property":"UnionPost"},{"counterexample":"((T (T E -2 0 E) 2 0 E) (T E -2 1 E))","property":"UnionModel"},{"counterexample":"((T (T E -2 0 E) 1 0 E) (T E 0 0 E) 1)","property":"DeleteUnion"},{"counterexample":"((T E 2 2 E) (T E -1 1 E) -1 0)","property":"InsertUnion"},{"counterexample":"((T E -1 3 E) (T E 3 1 E) -1 0)","property":"UnionDeleteInsert"},{"counterexample":"((T E 2 1 E) (T E 2 0 E) (T E 0 0 E))","property":"UnionUnionAssoc"}]}],"rbt":[{"mutations":["delete_4"],"tasks":[{"counterexample":"((T B (T B E -1 0 E) 0 3 (T B E 3 0 E)) -1 0)","property":"DeleteDelete"},{"counterexample":"((T B E 1 0 E) 0)","property":"DeleteModel"},{"counterexample":"((T B E 0 0 E) 1 0)","property":"DeletePost"},{"counterexample":"(E 0 1 0)","property":"DeleteInsert"},{"counterexample":"(E 0 0 0)","property":"InsertDelete"}]},{"mutations":["insert_1"],"tasks":[{"counterexample":"((T B E -1 1 E) 0 -1 0)","property":"InsertPost"},{"counterexample":"((T B E 1 0 E) 0 0)","property":"InsertModel"},{"counterexample":"((T B E 0 0 E) -3 -3 0)","property":"DeleteInsert"},{"counterexample":"(E 0 1 0 0)","property":"InsertInsert"}]},{"mutations":["insert_2"],"tasks":[{"counterexample":"((T B E -1 1 E) 0 0 0)","property":"InsertPost"},{"counterexample":"((T B E 0 0 E) 1 0)","property":"InsertModel"},{"counterexample":"(E 0 0 0)","property":"InsertDelete"},{"counterexample":"((T B E -1 0 E) 0 0 1)","property":"DeleteInsert"},{"counterexample":"(E 1 0 1 0)","property":"InsertInsert"}]},{"mutations":["insert_3"],"tasks":[{"counterexample":"((T B E 0 1 E) 0 0 0)","property":"InsertPost"},{"counterexample":"((T B E -1 1 E) -1 0)","property":"InsertModel"},{"counterexample":"(E 0 0 0)","property":"InsertDelete"},{"counterexample":"(E 3 3 0 1)","property":"InsertInsert"}]},{"mutations":["delete_5"],"tasks":[{"counterexample":"((T B (T B E -2 1 E) 0 0 (T B E 1 4 E)) 1)","property":"DeleteModel"},{"counterexample":"((T B E 3 0 (T R E 4 0 E)) 4 4)","property":"DeletePost"},{"counterexample":"((T B E -4 6 (T R E 9 0 E)) 9 -4)","property":"DeleteDelete"},{"counterexample":"((T B E 0 0 E) 1 1 0)","property":"DeleteInsert"}]},{"mutations":["miscolor_insert"],"tasks":[{"counterexample":"((T B E 0 0 E) 1 0)","property":"InsertValid"},{"counterexample":"((T B E 1 0 E) 0 0 0)","property":"DeleteInsert"}]},{"mutations":["miscolor_delete"],"tasks":[{"counterexample":"((T B E 0 0 (T R E 1 1 E)) 2)","property":"DeleteValid"}]},{"mutations":["miscolor_balLeft"],"tasks":[{"counterexample":"((T B (T B E -5 0 E) 0 0 (T R (T B E 2 2 E) 5 6 (T B E 6 1 E))) -5)","property":"DeleteValid"},{"counterexample":"((T B (T B E -2 6 E) -1 0 (T R (T B E 0 0 E) 3 0 (T B E 5 8 E))) 5 -2)","property":"DeleteDelete"}]},{"mutations":["miscolor_balRight"],"tasks":[{"counterexample":"((T B (T R (T B E -8 0 E) -2 0 (T B E 0 0 E)) 6 0 (T B E 7 6 E)) 7)","property":"DeleteValid"},{"counterexample":"((T B (T R (T B E -9 1 E) -8 0 (T B E 0 0 E)) 3 0 (T B E 6 5 E)) -9 6)","property":"DeleteDelete"}]},{"mutations":["miscolor_join_1"],"tasks":[{"counterexample":"((T B (T B (T R (T B E -12 2 E) -6 0 (T B E -3 0 E)) -2 0 (T R (T B (T R E 0 0 E) 3 0 E) 4 0 (T B E 5 4 E))) 6 3 (T B (T B E 8 8 E) 9 0 (T B E 10 0 E))) -2)","property":"DeleteValid"}]},{"mutations":["miscolor_join_2"],"tasks":[{"counterexample":"((T B (T B E -5 0 (T R E -4 1 E)) -1 0 (T B (T R E 2 0 E) 4 0 E)) -1)","property":"DeleteValid"},{"counterexample":"((T (B) (T (B) (E) 0 0 (E)) 1 0 (T (R) (T (B) (E) 2 0 (T (R) (E) 3 0 (E))) 4 0 (T (B) (E) 5 0 (E)))) 4 0)","property":"DeleteDelete"}]},{"mutations":["no_balance_insert_1"],"tasks":[{"counterexample":"((T B (T R E 1 1 E) 2 2 E) 0 0)","property":"InsertValid"},{"counterexample":"((T B (T R (T B E -8 0 E) 0 0 (T B E 1 0 (T R E 4 2 E))) 5 3 (T B E 7 4 E)) 7 2 0)","property":"DeleteInsert"},{"counterexample":"(E 0 0 0)","property":"InsertDelete"}]},{"mutations":["no_balance_insert_2"],"tasks":[{"counterexample":"((T B E -1 0 E) 0 0)","property":"InsertValid"},{"counterexample":"((T B E 0 0 E) 3 3 0)","property":"DeleteInsert"},{"counterexample":"(E 0 0 0)","property":"InsertDelete"}]}],"stlc":[{"mutations":["shift_var_none"],"tasks":[{"counterexample":"(Abs TBool (App (Abs TBool (Var 1)) (Bool #t)))","property":"SinglePreserve"},{"counterexample":"(Abs TBool (App (Abs TBool (Var 1)) (Bool #t)))","property":"MultiPreserve"}]},{"mutations":["shift_var_all"],"tasks":[{"counterexample":"(App (Abs TBool (Abs TBool (Var 0))) (Bool #t))","property":"SinglePreserve"},{"counterexample":"(App (Abs TBool (Abs TBool (Var 0))) (Bool #t))","property":"MultiPreserve"}]},{"mutations":["shift_var_leq"],"tasks":[{"counterexample":"(App (Abs TBool (App (Abs TBool (Abs (TFun TBool TBool) (Var 1))) (Var 0))) (Bool #t))","property":"SinglePreserve"},{"counterexample":"(App (Abs TBool (App (Abs TBool (Abs (TFun TBool TBool) (Var 1))) (Var 0))) (Bool #t))","property":"MultiPreserve"}]},{"mutations":["shift_abs_no_incr"],"tasks":[{"counterexample":"(App (Abs TBool (Abs TBool (Var 0))) (Bool #t))","property":"SinglePreserve"},{"counterexample":"(App (Abs TBool (Abs TBool (Var 0))) (Bool #t))","property":"MultiPreserve"}]},{"mutations":["subst_var_all"],"tasks":[{"counterexample":"(Abs (TFun TBool TBool) (App (Abs TBool (Var 1)) (Bool #t)))","property":"SinglePreserve"},{"counterexample":"(Abs (TFun TBool TBool) (App (Abs TBool (Var 1)) (Bool #t)))","property":"MultiPreserve"}]},{"mutations":["subst_var_none"],"tasks":[{"counterexample":"(App (Abs TBool (Var 0)) (Bool #t))","property":"SinglePreserve"},{"counterexample":"(App (Abs TBool (Var 0)) (Bool #t))","property":"MultiPreserve"}]},{"mutations":["subst_abs_no_shift"],"tasks":[{"counterexample":"(App (Abs TBool (App (Abs TBool (Abs (TFun TBool TBool) (Var 1))) (Var 0))) (Bool #t))","property":"SinglePreserve"},{"counterexample":"(App (Abs TBool (App (Abs TBool (Abs (TFun TBool TBool) (Var 1))) (Var 0))) (Bool #t))","property":"MultiPreserve"}]},{"mutations":["subst_abs_no_incr"],"tasks":[{"counterexample":"(App (Abs TBool (Abs (TFun TBool TBool) (Var 1))) (Bool #t))","property":"SinglePreserve"},{"counterexample":"(App (Abs TBool (Abs (TFun TBool TBool) (Var 1))) (Bool #t))","property":"MultiPreserve"}]},{"mutations":["substTop_no_shift"],"tasks":[{"counterexample":"(Abs TBool (App (Abs TBool (Var 1)) (Bool #t)))","property":"SinglePreserve"},{"counterexample":"(Abs TBool (App (Abs TBool (Var 1)) (Bool #t)))","property":"MultiPreserve"}]},{"mutations":["substTop_no_shift_back"],"tasks":[{"counterexample":"(Abs TBool (App (Abs TBool (Var 0)) (Var 0)))","property":"SinglePreserve"},{"counterexample":"(Abs TBool (App (Abs TBool (Var 0)) (Var 0)))","property":"MultiPreserve"}]}]};

 // Decompress metrics
 let METRICS = [];
 async function decompressMetrics() {
  const bin = Uint8Array.from(atob(METRICS_B64), c => c.charCodeAt(0));
  const ds = new DecompressionStream('gzip');
  const writer = ds.writable.getWriter();
  writer.write(bin);
  writer.close();
  const reader = ds.readable.getReader();
  const chunks = [];
  while (true) {
    const { done, value } = await reader.read();
    if (done) break;
    chunks.push(value);
  }
  const blob = new Blob(chunks);
  const text = await blob.text();
  METRICS = JSON.parse(text);
 }

 // ============================================================
 // UTILITIES
 // ============================================================
 function parseTime(s) {
  if (s === null || s === undefined) return NaN;
  if (typeof s === 'number') return s;
  s = String(s).trim();
  const m = s.match(/^([\d.]+)\s*(ns|us|µs|ms|s)$/);
  if (!m) return parseFloat(s);
  const v = parseFloat(m[1]);
  switch (m[2]) {
    case 'ns': return v / 1e9;
    case 'us': case 'µs': return v / 1e6;
    case 'ms': return v / 1e3;
    case 's': return v;
  }
  return NaN;
 }

 function formatTime(sec) {
  if (sec === null || sec === undefined || isNaN(sec)) return 'N/A';
  if (!isFinite(sec)) return 'Timeout';
  if (sec < 1e-6) return (sec * 1e9).toFixed(1) + ' ns';
  if (sec < 1e-3) return (sec * 1e6).toFixed(1) + ' µs';
  if (sec < 1) return (sec * 1e3).toFixed(2) + ' ms';
  return sec.toFixed(3) + ' s';
 }

 function formatNum(n) {
  if (n === null || n === undefined || isNaN(n)) return 'N/A';
  if (!isFinite(n)) return '\u221e';
  return Number(n).toLocaleString(undefined, {maximumFractionDigits: 2});
 }

 function mutKey(mutations) {
  if (!mutations || (Array.isArray(mutations) && mutations.length === 0)) return '(none)';
  if (Array.isArray(mutations)) return mutations.sort().join(', ');
  return String(mutations);
 }

 function statusNorm(s) { return (s || '').toLowerCase(); }

 function unique(arr, fn) {
  const s = new Set();
  for (const x of arr) { const v = fn(x); if (v !== undefined) s.add(v); }
  return [...s].sort();
 }

 function groupBy(arr, keyFn) {
  const m = new Map();
  for (const x of arr) {
    const k = keyFn(x);
    if (!m.has(k)) m.set(k, []);
    m.get(k).push(x);
  }
  return m;
 }

 function mean(arr) {
  if (!arr.length) return NaN;
  return arr.reduce((a,b) => a+b, 0) / arr.length;
 }

 function median(arr) {
  if (!arr.length) return NaN;
  const sorted = [...arr].sort((a,b) => a-b);
  const mid = Math.floor(sorted.length / 2);
  return sorted.length % 2 ? sorted[mid] : (sorted[mid-1] + sorted[mid]) / 2;
 }

 // Aggregate values respecting validity rules:
 // If mode is 'mean' and any trial in the cell is non-failing, mean is invalid -> return NaN.
 // If mode is 'median', always compute median of failing trials only.
 // `allTrials` = full set of trials for the cell, `vals` = values from failing trials only.
 function agg(vals, allTrials, mode) {
  const hasNonFailing = allTrials.some(m => m._status !== 'failed');
  if (mode === 'mean') {
    if (hasNonFailing) return NaN; // invalid mean
    return mean(vals);
  }
  // median mode — always use failing trials
  return median(vals);
 }

 // Format an aggregated value, marking invalid means
 function formatAggTime(val, allTrials, mode) {
  const hasNonFailing = allTrials.some(m => m._status !== 'failed');
  if (mode === 'mean' && hasNonFailing) return '<span class="invalid-mean" title="Some trials did not find a bug — mean is invalid">N/A*</span>';
  return formatTime(val);
 }

 function formatAggNum(val, allTrials, mode) {
  const hasNonFailing = allTrials.some(m => m._status !== 'failed');
  if (mode === 'mean' && hasNonFailing) return '<span class="invalid-mean" title="Some trials did not find a bug — mean is invalid">N/A*</span>';
  return formatNum(val);
 }

 // Toggle group helper — wires up a toggle group and returns a function to get the current mode
 function setupToggle(containerId, onChange) {
  const el = document.getElementById(containerId);
  if (!el) return () => 'mean';
  el.addEventListener('click', e => {
    const btn = e.target.closest('button');
    if (!btn) return;
    el.querySelectorAll('button').forEach(b => b.classList.remove('active'));
    btn.classList.add('active');
    if (onChange) onChange();
  });
  return () => (el.querySelector('button.active')?.dataset.mode || 'mean');
 }

 function parseMetrics() {
  for (const m of METRICS) {
    m._time = parseTime(m.time);
    m._shrinking_time = parseTime(m.shrinking_time);
    m._generation_time = parseTime(m.generation_time);
    m._execution_time = parseTime(m.execution_time);
    m._status = statusNorm(m.status);
    m._mutations = mutKey(m.mutations);
  }
 }

 // ============================================================
 // NAVIGATION
 // ============================================================
 const nav = document.getElementById('nav');
 nav.addEventListener('click', e => {
  if (e.target.tagName !== 'BUTTON') return;
  nav.querySelectorAll('button').forEach(b => b.classList.remove('active'));
  e.target.classList.add('active');
  document.querySelectorAll('.view').forEach(v => v.classList.remove('active'));
  document.getElementById('view-' + e.target.dataset.view).classList.add('active');
  location.hash = e.target.dataset.view;
  render(e.target.dataset.view);
 });

 // Handle hash on load
 const initialView = location.hash.slice(1) || 'overview';
 const rendered = new Set();

 function render(view) {
  if (rendered.has(view)) return;
  rendered.add(view);
  switch(view) {
    case 'overview': renderOverview(); break;
    case 'buckets': renderBuckets(); break;
    case 'strategies': renderStrategies(); break;
    case 'mutations': renderMutations(); break;
    case 'drilldown': renderDrilldown(); break;
    case 'rawdata': renderRawData(); break;
  }
 }

 // ============================================================
 // CHART.JS DEFAULTS
 // ============================================================
 Chart.defaults.color = '#8b949e';
 Chart.defaults.borderColor = '#30363d';
 Chart.defaults.font.family = '-apple-system, BlinkMacSystemFont, "Segoe UI", Helvetica, Arial, sans-serif';
 Chart.defaults.font.size = 12;
 Chart.defaults.plugins.legend.labels.boxWidth = 14;

 const PALETTE = ['#58a6ff','#3fb950','#d29922','#f85149','#bc8cff','#f778ba','#79c0ff','#56d364','#e3b341','#ff7b72','#d2a8ff','#ff9bce'];

 // ============================================================
 // OVERVIEW
 // ============================================================
 function renderOverview() {
  document.getElementById('exp-name').textContent = EXPERIMENT_NAME;
  document.getElementById('gen-time').textContent = GENERATED_AT;
  document.getElementById('metric-count').textContent = METRICS.length;

  const strategies = unique(METRICS, m => m.strategy);
  const workloads = unique(METRICS, m => m.workload);
  const properties = unique(METRICS, m => m.property);
  const languages = unique(METRICS, m => m.language);

  const cardsEl = document.getElementById('overview-cards');
  cardsEl.innerHTML = [
    { label: 'Records', value: METRICS.length },
    { label: 'Strategies', value: strategies.length },
    { label: 'Workloads', value: workloads.length },
    { label: 'Properties', value: properties.length },
    { label: 'Languages', value: languages.length },
    { label: 'Bug Found', value: METRICS.filter(m => m._status === 'failed').length },
  ].map(c => `<div class="card"><div class="label">${c.label}</div><div class="value">${c.value}</div></div>`).join('');

  // Summary table
  const groups = groupBy(METRICS, m => `${m.workload}|||${m.property}|||${m._mutations}`);

  // Precompute per-group data (mode-independent)
  const groupData = [];
  for (const [key, items] of groups) {
    const [workload, property, mutation] = key.split('|||');
    const strats = unique(items, m => m.strategy);
    const bugTrials = items.filter(m => m._status === 'failed');
    const bugRate = bugTrials.length / items.length;
    const times = bugTrials.map(m => m._time).filter(t => !isNaN(t));
    const tests = bugTrials.map(m => m.tests).filter(t => t != null);
    groupData.push({ workload, property, mutation, strats, items, bugTrials, bugRate, times, tests });
  }

  const tbody = document.querySelector('#overview-table tbody');
  let sortCol = 'workload', sortDir = 1;
  const getAggMode = setupToggle('overview-agg-toggle', renderTable);

  function renderTable() {
    const mode = getAggMode();
    // Update column headers
    const label = mode === 'mean' ? 'Mean' : 'Median';
    document.getElementById('overview-th-time').innerHTML = `${label} TTF <span class="sort-arrow">&#9650;</span>`;
    document.getElementById('overview-th-tests').innerHTML = `${label} ITF <span class="sort-arrow">&#9650;</span>`;

    const rows = groupData.map(g => {
      const aggTime = agg(g.times, g.items, mode);
      const aggTests = agg(g.tests, g.items, mode);
      return { ...g, strategies: g.strats.length, trials: g.items.length, aggTime, aggTests };
    });

    rows.sort((a,b) => {
      let va = a[sortCol], vb = b[sortCol];
      if (typeof va === 'string') return sortDir * va.localeCompare(vb);
      if (va == null || isNaN(va)) va = -Infinity;
      if (vb == null || isNaN(vb)) vb = -Infinity;
      return sortDir * (va - vb);
    });
    tbody.innerHTML = rows.map(r => `<tr>
      <td>${r.workload}</td>
      <td>${r.property}</td>
      <td>${r.mutation}</td>
      <td class="num">${r.strategies}</td>
      <td class="num">${r.trials}</td>
      <td class="num">${(r.bugRate*100).toFixed(1)}%</td>
      <td class="num">${formatAggTime(r.aggTime, r.items, mode)}</td>
      <td class="num">${formatAggNum(r.aggTests, r.items, mode)}</td>
    </tr>`).join('');
  }

  document.querySelectorAll('#overview-table th').forEach(th => {
    th.addEventListener('click', () => {
      const col = th.dataset.col;
      if (sortCol === col) sortDir *= -1; else { sortCol = col; sortDir = 1; }
      renderTable();
    });
  });

  renderTable();
 }

 // ============================================================
 // BUCKET CHARTS
 // ============================================================
 let bucketCharts = [];
 // Store computed bucket data for compare modal
 let bucketGroupData = new Map(); // key -> {bucketCounts, cellCount}

 function getCheckedGroupByFields() {
  return [...document.querySelectorAll('.bucket-groupby-cb:checked')].map(cb => cb.value);
 }

 function renderBuckets() {
  const triggerRebuild = () => { rendered.delete('buckets_inner'); rebuildBuckets(); };
  window._getBucketAgg = setupToggle('bucket-agg-toggle', triggerRebuild);
  rebuildBuckets();
  document.getElementById('bucket-apply').addEventListener('click', triggerRebuild);
  document.getElementById('bucket-metric').addEventListener('change', triggerRebuild);
  document.querySelectorAll('.bucket-groupby-cb').forEach(cb => cb.addEventListener('change', triggerRebuild));
  document.getElementById('bucket-compare-btn').addEventListener('click', openCompareModal);
 }

 function computeBucketCounts(metrics, metricField, thresholds, aggMode) {
  const cells = groupBy(metrics, m => `${m.property}|||${m._mutations}`);
  const bucketCounts = new Array(thresholds.length + 1).fill(0);

  for (const [, cellMetrics] of cells) {
    const anyTimeout = cellMetrics.some(m => m._status === 'timed_out');
    if (anyTimeout) {
      bucketCounts[thresholds.length]++;
      continue;
    }

    const failTrials = cellMetrics.filter(m => m._status === 'failed');
    let vals;
    if (metricField === 'time') {
      vals = failTrials.map(m => m._time).filter(t => !isNaN(t));
    } else {
      vals = failTrials.map(m => m.tests).filter(t => t != null);
    }

    const val = agg(vals, cellMetrics, aggMode);

    if (isNaN(val)) {
      bucketCounts[thresholds.length]++;
      continue;
    }

    let placed = false;
    for (let i = 0; i < thresholds.length; i++) {
      if (val <= thresholds[i]) {
        bucketCounts[i]++;
        placed = true;
        break;
      }
    }
    if (!placed) bucketCounts[thresholds.length]++;
  }
  return { bucketCounts, cellCount: cells.size };
 }

 function getBucketConfig() {
  const metricField = document.getElementById('bucket-metric').value;
  const thresholds = document.getElementById('bucket-thresholds').value
    .split(',').map(s => parseFloat(s.trim())).filter(n => !isNaN(n)).sort((a,b) => a-b);
  const aggMode = (window._getBucketAgg || (() => 'mean'))();
  const groupByFields = getCheckedGroupByFields();

  const bucketLabels = [];
  for (let i = 0; i < thresholds.length; i++) {
    const lo = i === 0 ? 0 : thresholds[i-1];
    const hi = thresholds[i];
    if (metricField === 'time') {
      bucketLabels.push(`${formatTime(lo)} - ${formatTime(hi)}`);
    } else {
      bucketLabels.push(`${formatNum(lo)} - ${formatNum(hi)}`);
    }
  }
  bucketLabels.push('Timeout');

  return { metricField, thresholds, aggMode, groupByFields, bucketLabels };
 }

 const BUCKET_COLORS = ['#3fb950','#58a6ff','#d29922','#f0883e','#f85149','#8b949e'];

 function rebuildBuckets() {
  if (rendered.has('buckets_inner')) return;
  rendered.add('buckets_inner');

  for (const c of bucketCharts) c.destroy();
  bucketCharts = [];
  bucketGroupData = new Map();

  const { metricField, thresholds, aggMode, groupByFields, bucketLabels } = getBucketConfig();

  if (!groupByFields.length) {
    document.getElementById('bucket-charts').innerHTML = '<p style="color:var(--text2)">Select at least one group-by field.</p>';
    return;
  }

  // Sort group-by fields: workload first, then language, strategy, cross
  const fieldOrder = ['workload', 'language', 'strategy', 'cross'];
  const sortedFields = [...groupByFields].sort((a, b) => fieldOrder.indexOf(a) - fieldOrder.indexOf(b));

  function compositeKey(m) {
    return sortedFields.map(f => {
      if (f === 'cross') return m.cross ? 'cross' : 'no-cross';
      return m[f] ?? '?';
    }).join(' / ');
  }

  const outerGroups = groupBy(METRICS, compositeKey);
  const container = document.getElementById('bucket-charts');
  container.innerHTML = '';

  // Collect all data for a single combined chart
  const allKeys = [];
  for (const [outerKey, outerMetrics] of outerGroups) {
    const { bucketCounts, cellCount } = computeBucketCounts(outerMetrics, metricField, thresholds, aggMode);
    bucketGroupData.set(outerKey, { bucketCounts, cellCount, metrics: outerMetrics });
    allKeys.push(outerKey);
  }
  allKeys.sort();

  // Render as one stacked horizontal bar chart with all groups
  const wrap = document.createElement('div');
  wrap.className = 'chart-container';
  wrap.style.padding = '12px 16px';
  const chartHeight = Math.max(120, allKeys.length * 56 + 40);
  wrap.innerHTML = `<canvas style="height:${chartHeight}px"></canvas>`;
  container.appendChild(wrap);

  const ctx = wrap.querySelector('canvas').getContext('2d');
  const datasets = bucketLabels.map((label, i) => ({
    label,
    data: allKeys.map(key => bucketGroupData.get(key).bucketCounts[i]),
    backgroundColor: BUCKET_COLORS[i % BUCKET_COLORS.length],
  }));

  const chart = new Chart(ctx, {
    type: 'bar',
    data: { labels: allKeys, datasets },
    options: {
      indexAxis: 'y',
      responsive: true,
      maintainAspectRatio: false,
      scales: {
        x: { stacked: true, title: { display: true, text: '# cells' } },
        y: { stacked: true, ticks: { font: { size: 11 } } },
      },
      plugins: {
        tooltip: { callbacks: { label: ctx => `${ctx.dataset.label}: ${ctx.raw}` } },
        legend: { position: 'bottom', labels: { boxWidth: 12, font: { size: 11 } } },
      },
      barPercentage: 0.7,
    }
  });
  bucketCharts.push(chart);
 }

 // ---- Compare Modal ----
 let compareChart = null;

 function openCompareModal() {
  const groups = [...bucketGroupData.keys()];
  if (groups.length < 2) {
    alert('Need at least 2 groups to compare.');
    return;
  }

  const { bucketLabels } = getBucketConfig();

  const overlay = document.createElement('div');
  overlay.className = 'modal-overlay';
  overlay.innerHTML = `<div class="modal" style="min-width:750px;">
    <div class="modal-header">
      <h2>Compare Bucket Charts</h2>
      <button class="modal-close">&times;</button>
    </div>
    <div style="margin-bottom:12px;max-height:200px;overflow-y:auto;border:1px solid var(--border);border-radius:6px;padding:8px;" id="compare-checklist"></div>
    <div style="display:flex;gap:8px;margin-bottom:16px;">
      <button class="btn" id="compare-select-all">Select All</button>
      <button class="btn" id="compare-select-none">Select None</button>
    </div>
    <div id="compare-chart-wrap" style="min-height:100px;"></div>
  </div>`;
  document.body.appendChild(overlay);

  // Populate checklist
  const checklist = overlay.querySelector('#compare-checklist');
  checklist.innerHTML = groups.map(g =>
    `<label style="display:block;padding:3px 0;font-size:13px;cursor:pointer;">` +
    `<input type="checkbox" class="compare-group-cb" value="${g}" style="margin-right:8px;">${g}` +
    `</label>`
  ).join('');

  // Close handlers
  function closeModal() { if (compareChart) { compareChart.destroy(); compareChart = null; } overlay.remove(); }
  overlay.querySelector('.modal-close').addEventListener('click', closeModal);
  overlay.addEventListener('click', e => { if (e.target === overlay) closeModal(); });

  // Select all/none
  overlay.querySelector('#compare-select-all').addEventListener('click', () => {
    checklist.querySelectorAll('input').forEach(cb => cb.checked = true);
    rebuildCompare();
  });
  overlay.querySelector('#compare-select-none').addEventListener('click', () => {
    checklist.querySelectorAll('input').forEach(cb => cb.checked = false);
    rebuildCompare();
  });

  // Rebuild chart on any checkbox change
  checklist.addEventListener('change', rebuildCompare);

  function rebuildCompare() {
    const selected = [...checklist.querySelectorAll('input:checked')].map(cb => cb.value);
    const wrap = overlay.querySelector('#compare-chart-wrap');
    if (compareChart) { compareChart.destroy(); compareChart = null; }

    if (selected.length < 2) {
      wrap.innerHTML = '<p style="color:var(--text2);font-size:13px;">Select at least 2 groups.</p>';
      return;
    }

    const chartH = Math.max(120, selected.length * 28 + 50);
    wrap.innerHTML = `<canvas style="height:${chartH}px"></canvas>`;
    const ctx = wrap.querySelector('canvas').getContext('2d');
    const datasets = bucketLabels.map((label, i) => ({
      label,
      data: selected.map(key => {
        const d = bucketGroupData.get(key);
        return d ? d.bucketCounts[i] : 0;
      }),
      backgroundColor: BUCKET_COLORS[i % BUCKET_COLORS.length],
    }));

    compareChart = new Chart(ctx, {
      type: 'bar',
      data: { labels: selected, datasets },
      options: {
        indexAxis: 'y',
        responsive: true,
        maintainAspectRatio: false,
        scales: { x: { stacked: true, title: { display: true, text: '# cells' } }, y: { stacked: true } },
        plugins: {
          tooltip: { callbacks: { label: ctx => `${ctx.dataset.label}: ${ctx.raw}` } }
        }
      }
    });
  }
 }

 // ============================================================
 // STRATEGY COMPARISON
 // ============================================================
 let stratCharts = [];

 function renderStrategies() {
  const workloads = unique(METRICS, m => m.workload);
  const sel = document.getElementById('strat-workload');
  sel.innerHTML = workloads.map(w => `<option value="${w}">${w}</option>`).join('');
  sel.addEventListener('change', rebuildStrategies);
  document.getElementById('strat-metric').addEventListener('change', rebuildStrategies);
  window._getStratAgg = setupToggle('strat-agg-toggle', rebuildStrategies);
  window._getStratScale = setupToggle('strat-scale-toggle', rebuildStrategies);
  rebuildStrategies();
 }

 function getMetricVals(metrics, metricField) {
  if (metricField === 'time') return metrics.map(m => m._time);
  if (metricField === 'shrinking_time') return metrics.map(m => m._shrinking_time);
  if (metricField === 'generation_time') return metrics.map(m => m._generation_time);
  if (metricField === 'execution_time') return metrics.map(m => m._execution_time);
  return metrics.map(m => m[metricField]);
 }

 function rebuildStrategies() {
  for (const c of stratCharts) c.destroy();
  stratCharts = [];

  const wl = document.getElementById('strat-workload').value;
  const metricField = document.getElementById('strat-metric').value;
  const aggMode = (window._getStratAgg || (() => 'mean'))();
  const wlMetrics = METRICS.filter(m => m.workload === wl);
  const strategies = unique(wlMetrics, m => m.strategy);
  const properties = unique(wlMetrics, m => m.property);

  // Bug finding rate per strategy (not affected by agg mode)
  const bugRates = strategies.map(s => {
    const sm = wlMetrics.filter(m => m.strategy === s);
    const cells = groupBy(sm, m => `${m.property}|||${m._mutations}`);
    let found = 0, total = 0;
    for (const [, cellMetrics] of cells) {
      total++;
      const anyBug = cellMetrics.some(m => m._status === 'failed');
      if (anyBug) found++;
    }
    return total ? (found / total * 100) : 0;
  });

  const bugCtx = document.getElementById('strat-bugrate-chart').getContext('2d');
  stratCharts.push(new Chart(bugCtx, {
    type: 'bar',
    data: {
      labels: strategies,
      datasets: [{
        label: 'Bug Finding Rate (%)',
        data: bugRates,
        backgroundColor: strategies.map((_, i) => PALETTE[i % PALETTE.length]),
      }]
    },
    options: {
      responsive: true,
      plugins: { legend: { display: false } },
      scales: { y: { beginAtZero: true, max: 100, title: { display: true, text: '%' } } }
    }
  }));

  // Metric per strategy
  const aggLabel = aggMode === 'mean' ? 'Mean' : 'Median';
  const metricTitleMap = {
    time: 'Time', tests: 'Tests', shrinking_time: 'Shrinking Time',
    generation_time: 'Generation Time', execution_time: 'Execution Time', discards: 'Discards',
  };
  const metricName = metricTitleMap[metricField] || metricField;
  document.getElementById('strat-metric-title').textContent = `${aggLabel} ${metricName} by Strategy`;

  const isTimeMetric = ['time','shrinking_time','generation_time','execution_time'].includes(metricField);
  const scaleRaw = (window._getStratScale || (() => 'linear'))();
  const scaleType = scaleRaw === 'log' ? 'logarithmic' : 'linear';

  // Compute metric values with fallback info for invalid means
  const metricEntries = strategies.map(s => {
    const allTrials = wlMetrics.filter(m => m.strategy === s);
    const failTrials = allTrials.filter(m => m._status === 'failed');
    let vals = getMetricVals(failTrials, metricField);
    vals = vals.filter(v => v != null && !isNaN(v) && isFinite(v));
    const v = agg(vals, allTrials, aggMode);
    const invalid = isNaN(v);
    const fallback = invalid ? median(vals) : v;
    return { value: v, display: isNaN(fallback) ? 0 : fallback, invalid };
  });

  const metricCtx = document.getElementById('strat-metric-chart').getContext('2d');
  stratCharts.push(new Chart(metricCtx, {
    type: 'bar',
    data: {
      labels: strategies,
      datasets: [{
        label: `${aggLabel} ${metricName}`,
        data: metricEntries.map(e => e.display),
        backgroundColor: metricEntries.map((e, i) => e.invalid ? 'rgba(210,153,34,0.5)' : PALETTE[i % PALETTE.length]),
        borderColor: metricEntries.map((e, i) => e.invalid ? '#d29922' : PALETTE[i % PALETTE.length]),
        borderWidth: metricEntries.map(e => e.invalid ? 2 : 0),
      }]
    },
    options: {
      responsive: true,
      plugins: {
        legend: { display: false },
        tooltip: {
          callbacks: {
            label: ctx => {
              const e = metricEntries[ctx.dataIndex];
              if (e.invalid) {
                const fmtVal = isTimeMetric ? formatTime(e.display) : formatNum(e.display);
                return `Mean invalid — showing median: ${fmtVal}`;
              }
              return isTimeMetric ? formatTime(e.display) : formatNum(e.display);
            }
          }
        }
      },
      scales: {
        y: {
          type: scaleType,
          beginAtZero: scaleType === 'linear',
          title: { display: true, text: isTimeMetric ? 'seconds' : metricField },
          ticks: isTimeMetric ? { callback: v => formatTime(v) } : {}
        }
      }
    }
  }));

  // Distribution: grouped bar per property, one bar per strategy
  document.getElementById('strat-dist-title').textContent = `${aggLabel} ${metricName} Distribution by Strategy & Property`;
  const distCtx = document.getElementById('strat-dist-chart').getContext('2d');

  // Track invalidity per (strategy, property) for tooltips
  const distInvalid = strategies.map(s => properties.map(p => {
    const allTrials = wlMetrics.filter(m => m.strategy === s && m.property === p);
    return allTrials.some(m => m._status !== 'failed');
  }));

  const distDatasets = strategies.map((s, si) => {
    const data = properties.map((p, pi) => {
      const allTrials = wlMetrics.filter(m => m.strategy === s && m.property === p);
      const failTrials = allTrials.filter(m => m._status === 'failed');
      let vals = getMetricVals(failTrials, metricField);
      vals = vals.filter(v => v != null && !isNaN(v) && isFinite(v));
      const v = agg(vals, allTrials, aggMode);
      if (isNaN(v)) {
        const fb = median(vals);
        return isNaN(fb) ? 0 : fb;
      }
      return v;
    });
    const bgColors = properties.map((_, pi) =>
      distInvalid[si][pi] && aggMode === 'mean' ? 'rgba(210,153,34,0.5)' : PALETTE[si % PALETTE.length]
    );
    const borderColors = properties.map((_, pi) =>
      distInvalid[si][pi] && aggMode === 'mean' ? '#d29922' : PALETTE[si % PALETTE.length]
    );
    const borderWidths = properties.map((_, pi) =>
      distInvalid[si][pi] && aggMode === 'mean' ? 2 : 0
    );
    return { label: s, data, backgroundColor: bgColors, borderColor: borderColors, borderWidth: borderWidths };
  });

  stratCharts.push(new Chart(distCtx, {
    type: 'bar',
    data: { labels: properties, datasets: distDatasets },
    options: {
      responsive: true,
      plugins: {
        tooltip: {
          callbacks: {
            label: ctx => {
              const si = strategies.indexOf(ctx.dataset.label);
              const pi = ctx.dataIndex;
              const inv = si >= 0 && distInvalid[si] && distInvalid[si][pi] && aggMode === 'mean';
              const fmtVal = isTimeMetric ? formatTime(ctx.raw) : formatNum(ctx.raw);
              if (inv) return `${ctx.dataset.label}: mean invalid — median: ${fmtVal}`;
              return `${ctx.dataset.label}: ${fmtVal}`;
            }
          }
        }
      },
      scales: {
        y: {
          type: scaleType,
          beginAtZero: scaleType === 'linear',
          title: { display: true, text: isTimeMetric ? 'seconds' : metricField },
          ticks: isTimeMetric ? { callback: v => formatTime(v) } : {}
        }
      }
    }
  }));
 }

 // ============================================================
 // MUTATION MATRIX
 // ============================================================

 // Build valid (mutation, property) task set from WORKLOAD_DOCS
 // Returns a Set of "mutation|||property" keys for the given workload, or null if no docs found
 function getValidTasks(workload) {
  const wlLower = workload.toLowerCase();
  const doc = WORKLOAD_DOCS[wlLower];
  if (!doc || !Array.isArray(doc)) return null;
  const tasks = new Set();
  for (const entry of doc) {
    const muts = entry.mutations || [];
    const mutKey = muts.length ? muts.sort().join(', ') : '(none)';
    for (const task of (entry.tasks || [])) {
      tasks.add(`${mutKey}|||${task.property}`);
    }
  }
  return tasks;
 }

 function renderMutations() {
  const workloads = unique(METRICS, m => m.workload);
  const sel = document.getElementById('mut-workload');
  sel.innerHTML = ['<option value="(all)">All workloads</option>'].concat(workloads.map(w => `<option value="${w}">${w}</option>`)).join('');
  sel.addEventListener('change', rebuildMutations);
  rebuildMutations();
 }

 function rebuildMutations() {
  const wl = document.getElementById('mut-workload').value;
  const filtered = wl === '(all)' ? METRICS : METRICS.filter(m => m.workload === wl);
  const strategies = unique(filtered, m => m.strategy);

  // Get valid tasks from docs (when a single workload is selected)
  const validTasks = wl !== '(all)' ? getValidTasks(wl) : null;

  // Collect (mutation, property) pairs — either from docs or from data
  let taskPairs; // array of {mutation, property}
  if (validTasks && validTasks.size > 0) {
    taskPairs = [...validTasks].map(k => {
      const [mutation, property] = k.split('|||');
      return { mutation, property };
    });
  } else {
    // Fallback: derive from data, filtering out (none) mutations
    const seen = new Set();
    taskPairs = [];
    for (const m of filtered) {
      if (m._mutations === '(none)') continue;
      const key = `${m._mutations}|||${m.property}`;
      if (!seen.has(key)) {
        seen.add(key);
        taskPairs.push({ mutation: m._mutations, property: m.property });
      }
    }
  }

  if (!taskPairs.length) {
    document.getElementById('mutation-matrix-wrap').innerHTML = '<p style="color:var(--text2)">No mutation tasks found for this workload.</p>';
    return;
  }

  // Sort by mutation then property
  taskPairs.sort((a, b) => a.mutation.localeCompare(b.mutation) || a.property.localeCompare(b.property));

  // Rows: (property, mutation) from tasks, Columns: strategies
  let html = '<table><thead><tr><th>Property</th><th>Mutation</th>';
  for (const s of strategies) html += `<th style="text-align:center">${s}</th>`;
  html += '</tr></thead><tbody>';

  for (const { mutation: mut, property: prop } of taskPairs) {
    html += `<tr><td>${prop}</td><td>${mut}</td>`;
    for (const s of strategies) {
      const trials = filtered.filter(m => m.property === prop && m._mutations === mut && m.strategy === s);
      if (!trials.length) {
        html += '<td style="text-align:center;color:var(--text2)">-</td>';
        continue;
      }
      const bugs = trials.filter(m => m._status === 'failed').length;
      const rate = bugs / trials.length;
      const pct = (rate * 100).toFixed(0);
      let bg;
      if (rate >= 1) bg = 'rgba(63,185,80,0.3)';
      else if (rate > 0) bg = 'rgba(210,153,34,0.3)';
      else bg = 'rgba(248,81,73,0.3)';
      html += `<td style="text-align:center;background:${bg}" title="${bugs}/${trials.length} trials">${pct}%</td>`;
    }
    html += '</tr>';
  }
  html += '</tbody></table>';
  document.getElementById('mutation-matrix-wrap').innerHTML = html;
 }

 // ============================================================
 // DRILL-DOWN
 // ============================================================
 let ddCharts = [];

 function renderDrilldown() {
  const workloads = unique(METRICS, m => m.workload);
  const selW = document.getElementById('dd-workload');
  selW.innerHTML = workloads.map(w => `<option value="${w}">${w}</option>`).join('');

  function updateFilters() {
    const wl = selW.value;
    const wlM = METRICS.filter(m => m.workload === wl);
    const props = unique(wlM, m => m.property);
    document.getElementById('dd-property').innerHTML = props.map(p => `<option value="${p}">${p}</option>`).join('');
    updateMutations();
  }

  function updateMutations() {
    const wl = selW.value;
    const prop = document.getElementById('dd-property').value;
    const filtered = METRICS.filter(m => m.workload === wl && m.property === prop);
    const muts = unique(filtered, m => m._mutations);
    document.getElementById('dd-mutation').innerHTML = muts.map(m => `<option value="${m}">${m}</option>`).join('');
    updateStrategies();
  }

  function updateStrategies() {
    const wl = selW.value;
    const prop = document.getElementById('dd-property').value;
    const mut = document.getElementById('dd-mutation').value;
    const filtered = METRICS.filter(m => m.workload === wl && m.property === prop && m._mutations === mut);
    const strats = unique(filtered, m => m.strategy);
    document.getElementById('dd-strategy').innerHTML = ['<option value="(all)">All</option>'].concat(strats.map(s => `<option value="${s}">${s}</option>`)).join('');
    rebuildDrilldown();
  }

  selW.addEventListener('change', updateFilters);
  document.getElementById('dd-property').addEventListener('change', updateMutations);
  document.getElementById('dd-mutation').addEventListener('change', updateStrategies);
  document.getElementById('dd-strategy').addEventListener('change', rebuildDrilldown);

  updateFilters();
 }

 function rebuildDrilldown() {
  for (const c of ddCharts) c.destroy();
  ddCharts = [];

  const wl = document.getElementById('dd-workload').value;
  const prop = document.getElementById('dd-property').value;
  const mut = document.getElementById('dd-mutation').value;
  const strat = document.getElementById('dd-strategy').value;

  let filtered = METRICS.filter(m => m.workload === wl && m.property === prop && m._mutations === mut);
  if (strat !== '(all)') filtered = filtered.filter(m => m.strategy === strat);

  // Sort by trial
  filtered.sort((a,b) => (a.trial || 0) - (b.trial || 0));

  // Table
  const tbody = document.querySelector('#dd-table tbody');
  tbody.innerHTML = filtered.map(m => `<tr>
    <td class="num">${m.trial ?? '-'}</td>
    <td class="status-${m._status}">${m._status}</td>
    <td class="num">${formatTime(m._time)}</td>
    <td class="num">${m.tests ?? '-'}</td>
    <td class="num">${m.discards ?? '-'}</td>
    <td class="num">${formatTime(m._shrinking_time)}</td>
    <td class="num">${formatTime(m._generation_time)}</td>
    <td class="num">${formatTime(m._execution_time)}</td>
    <td style="max-width:200px;overflow:hidden;text-overflow:ellipsis;white-space:nowrap;" title="${(m.counterexample||'').replace(/"/g,'&quot;')}">${m.counterexample || '-'}</td>
  </tr>`).join('');

  // Charts by strategy
  const byStrat = groupBy(filtered, m => m.strategy);
  const stratNames = [...byStrat.keys()];

  // Time chart
  const timeCtx = document.getElementById('dd-time-chart').getContext('2d');
  ddCharts.push(new Chart(timeCtx, {
    type: 'bar',
    data: {
      labels: filtered.map(m => `${m.strategy} T${m.trial ?? '?'}`),
      datasets: [{
        label: 'Time',
        data: filtered.map(m => m._time),
        backgroundColor: filtered.map(m => {
          const si = stratNames.indexOf(m.strategy);
          return PALETTE[si % PALETTE.length];
        }),
      }]
    },
    options: {
      responsive: true,
      plugins: {
        legend: { display: false },
        tooltip: { callbacks: { label: ctx => formatTime(ctx.raw) } }
      },
      scales: { y: { beginAtZero: true, ticks: { callback: v => formatTime(v) } } }
    }
  }));

  // Tests chart
  const testsCtx = document.getElementById('dd-tests-chart').getContext('2d');
  ddCharts.push(new Chart(testsCtx, {
    type: 'bar',
    data: {
      labels: filtered.map(m => `${m.strategy} T${m.trial ?? '?'}`),
      datasets: [{
        label: 'Tests',
        data: filtered.map(m => m.tests),
        backgroundColor: filtered.map(m => {
          const si = stratNames.indexOf(m.strategy);
          return PALETTE[si % PALETTE.length];
        }),
      }]
    },
    options: {
      responsive: true,
      plugins: { legend: { display: false } },
      scales: { y: { beginAtZero: true } }
    }
  }));
 }

 // ============================================================
 // RAW DATA
 // ============================================================
 const RAW_COLS = ['workload','property','strategy','mutations','status','trial','time','tests','discards','shrinking_time','generation_time','execution_time','timeout','timestamp','counterexample'];
 let rawFilters = {};
 let rawSort = { col: null, dir: 1 };
 let rawPage = 0;

 function renderRawData() {
  // Build header
  const headerRow = document.getElementById('raw-header');
  const filterRow = document.getElementById('raw-filters');
  headerRow.innerHTML = RAW_COLS.map(c => `<th data-col="${c}">${c} <span class="sort-arrow">&#9650;</span></th>`).join('');
  filterRow.innerHTML = RAW_COLS.map(c => `<th><input type="text" placeholder="filter..." data-col="${c}"></th>`).join('');

  headerRow.querySelectorAll('th').forEach(th => {
    th.addEventListener('click', () => {
      const col = th.dataset.col;
      if (rawSort.col === col) rawSort.dir *= -1; else { rawSort.col = col; rawSort.dir = 1; }
      rebuildRawTable();
    });
  });

  filterRow.querySelectorAll('input').forEach(inp => {
    inp.addEventListener('input', () => {
      rawFilters[inp.dataset.col] = inp.value.toLowerCase();
      rawPage = 0;
      rebuildRawTable();
    });
  });

  document.getElementById('raw-pagesize').addEventListener('change', () => { rawPage = 0; rebuildRawTable(); });

  rebuildRawTable();
 }

 function rebuildRawTable() {
  let data = METRICS.slice();

  // Filter
  for (const [col, val] of Object.entries(rawFilters)) {
    if (!val) continue;
    data = data.filter(m => {
      let cv;
      if (col === 'mutations') cv = m._mutations;
      else if (col === 'time') cv = formatTime(m._time);
      else if (col === 'shrinking_time') cv = formatTime(m._shrinking_time);
      else if (col === 'generation_time') cv = formatTime(m._generation_time);
      else if (col === 'execution_time') cv = formatTime(m._execution_time);
      else cv = String(m[col] ?? '');
      return cv.toLowerCase().includes(val);
    });
  }

  // Sort
  if (rawSort.col) {
    const col = rawSort.col;
    data.sort((a,b) => {
      let va, vb;
      if (['time','shrinking_time','generation_time','execution_time'].includes(col)) {
        va = a['_'+col] ?? -Infinity; vb = b['_'+col] ?? -Infinity;
      } else if (col === 'mutations') {
        va = a._mutations; vb = b._mutations;
      } else {
        va = a[col]; vb = b[col];
      }
      if (typeof va === 'string') return rawSort.dir * va.localeCompare(String(vb || ''));
      if (va == null) va = -Infinity;
      if (vb == null) vb = -Infinity;
      return rawSort.dir * (va - vb);
    });
  }

  // Paginate
  const pageSize = parseInt(document.getElementById('raw-pagesize').value) || 0;
  const totalRows = data.length;
  const pageData = pageSize ? data.slice(rawPage * pageSize, (rawPage + 1) * pageSize) : data;
  const totalPages = pageSize ? Math.ceil(totalRows / pageSize) : 1;

  document.getElementById('raw-info').textContent = `Showing ${pageData.length} of ${totalRows} records`;

  const tbody = document.querySelector('#raw-table tbody');
  tbody.innerHTML = pageData.map(m => '<tr>' + RAW_COLS.map(c => {
    let v;
    if (c === 'mutations') v = m._mutations;
    else if (c === 'time') v = formatTime(m._time);
    else if (c === 'shrinking_time') v = formatTime(m._shrinking_time);
    else if (c === 'generation_time') v = formatTime(m._generation_time);
    else if (c === 'execution_time') v = formatTime(m._execution_time);
    else if (c === 'status') return `<td class="status-${m._status}">${m._status}</td>`;
    else v = m[c] ?? '';
    const isNum = ['trial','tests','discards','timeout'].includes(c);
    return `<td${isNum ? ' class="num"' : ''}>${v}</td>`;
  }).join('') + '</tr>').join('');

  // Pagination
  const pagEl = document.getElementById('raw-pagination');
  if (totalPages <= 1) { pagEl.innerHTML = ''; return; }
  let pagHtml = `<button class="btn" ${rawPage === 0 ? 'disabled' : ''} onclick="rawPage=0;rebuildRawTable()">&#171;</button>`;
  pagHtml += `<button class="btn" ${rawPage === 0 ? 'disabled' : ''} onclick="rawPage--;rebuildRawTable()">&#8249;</button>`;
  pagHtml += `<span>Page ${rawPage+1} of ${totalPages}</span>`;
  pagHtml += `<button class="btn" ${rawPage >= totalPages-1 ? 'disabled' : ''} onclick="rawPage++;rebuildRawTable()">&#8250;</button>`;
  pagHtml += `<button class="btn" ${rawPage >= totalPages-1 ? 'disabled' : ''} onclick="rawPage=${totalPages-1};rebuildRawTable()">&#187;</button>`;
  pagEl.innerHTML = pagHtml;
 }

 // Make pagination functions global
 window.rawPage = rawPage;
 Object.defineProperty(window, 'rawPage', {
  get() { return rawPage; },
  set(v) { rawPage = v; }
 });
 window.rebuildRawTable = rebuildRawTable;

 // ============================================================
 // INIT
 // ============================================================
 document.addEventListener('DOMContentLoaded', async () => {
  await decompressMetrics();
  parseMetrics();
  // Activate initial view from hash
  const btn = nav.querySelector(`button[data-view="${initialView}"]`);
  if (btn) btn.click(); else render('overview');
 });
 </script>
 </body>
 </html>
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