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48
49<div style="background:#a33;color:#fff;text-align:center;padding:6px;font-size:13px;font-weight:700;letter-spacing:0.1em;text-transform:uppercase;margin-bottom:10px;">DRAFT — Do not circulate without permission</div>
50
51<h1>Servo Baseline Readiness</h1>
52<div class="byline">Dietrich Ayala — dietrich@webtransitions.org — <a href="https://webtransitions.org">webtransitions.org</a></div>
53<p class="subtitle">Data as of February 13, 2026 — measuring Servo against Baseline "Widely Available" (BWA) web features</p>
54
55<div class="metric">
56 <div class="metric-item">
57 <div class="metric-value" style="color:#a33">22 <span style="font-size:20px;color:#686868">vs 52</span></div>
58 <div class="metric-label">Web Feature Velocity Gap<br>Servo completions/yr vs BWA growth/yr</div>
59 </div>
60 <div class="metric-item">
61 <div class="metric-value" style="color:rgb(71,11,0)">35 FTE</div>
62 <div class="metric-label">Velocity Parity<br>€5.3M/yr — €15.8M over 3yr</div>
63 </div>
64 <div class="metric-item">
65 <div class="metric-value" style="color:#8a5a00">19.8% <span style="font-size:20px;color:#686868">(87/439)</span></div>
66 <div class="metric-label">Current Readiness<br>(measurable features ≥95%)</div>
67 </div>
68 <div class="metric-item">
69 <div class="metric-value" style="color:#686868">~80%</div>
70 <div class="metric-label">Ceiling at 13 FTE<br>Web outgrows Servo</div>
71 </div>
72 <div class="metric-item">
73 <div class="metric-value" style="color:rgb(71,11,0)">593 <span style="font-size:20px;color:#686868">→ ~749</span></div>
74 <div class="metric-label">BWA Features<br>today → by 2029 (~52/yr)</div>
75 </div>
76</div>
77
78<div class="grid">
79
80<div class="card">
81 <h3>WPT Score Trajectory</h3>
82 <div class="chart-container"><canvas id="wptTrajectory"></canvas></div>
83</div>
84
85<div class="card">
86 <h3>Feature Score Distribution Over Time</h3>
87 <div class="chart-container"><canvas id="distribution"></canvas></div>
88</div>
89
90<div class="card">
91 <h3>Baseline Readiness by Year (Cumulative)</h3>
92 <div class="chart-container"><canvas id="byYear"></canvas></div>
93</div>
94
95<div class="card">
96 <h3>Commits & Contributors</h3>
97 <div class="chart-container"><canvas id="commits"></canvas></div>
98</div>
99
100<div class="card">
101 <h3>Projection: Features Fully Supported (Static Target)</h3>
102 <div class="chart-container"><canvas id="projections"></canvas></div>
103</div>
104
105<div class="card">
106 <h3>Moving Target: Servo vs Growing BWA Set</h3>
107 <div class="chart-container"><canvas id="movingTarget"></canvas></div>
108</div>
109
110<div class="card">
111 <h3>Stalled Features by Platform Area</h3>
112 <div class="chart-container"><canvas id="stalledDonut"></canvas></div>
113</div>
114
115<div class="card full">
116 <h3>Top 25 Regressions (Widely Available Features)</h3>
117 <div class="chart-container tall"><canvas id="regressions"></canvas></div>
118</div>
119
120<div class="card full">
121 <h3>Feature Landscape: Score vs Velocity</h3>
122 <div class="chart-container tall"><canvas id="scatter"></canvas></div>
123</div>
124
125</div>
126
127<div class="grid">
128<div class="card full">
129 <h3>Interactive Projection & Cost Calculator</h3>
130 <div style="display:flex;gap:40px;flex-wrap:wrap;margin-bottom:20px;">
131 <div style="flex:1;min-width:260px;">
132 <label style="display:block;color:#666;font-size:13px;margin-bottom:6px;">Full-Time Equivalents (FTE)</label>
133 <input type="range" id="calcContrib" min="1" max="100" value="13" style="width:100%;accent-color:rgb(71,11,0);">
134 <div style="display:flex;justify-content:space-between;font-size:12px;color:#686868;"><span>1</span><span id="calcContribVal" style="color:rgb(71,11,0);font-size:16px;font-weight:600;">13</span><span>100</span></div>
135 <div style="font-size:11px;color:#686868;margin-top:4px;">Current: ~13 FTE from 115 unique authors (9 core at ≥50% FTE). Measured as commits per author over 7 months, where 1 FTE = ~22 commits/month. Bots excluded.</div>
136 </div>
137 <div style="flex:1;min-width:260px;">
138 <label style="display:block;color:#666;font-size:13px;margin-bottom:6px;">Avg Annual Salary (EUR)</label>
139 <input type="range" id="calcSalary" min="50000" max="400000" step="10000" value="200000" style="width:100%;accent-color:rgb(71,11,0);">
140 <div style="display:flex;justify-content:space-between;font-size:12px;color:#686868;"><span>€50k</span><span id="calcSalaryVal" style="color:rgb(71,11,0);font-size:16px;font-weight:600;">€200k</span><span>€400k</span></div>
141 </div>
142 <div style="flex:1;min-width:260px;">
143 <label style="display:block;color:#666;font-size:13px;margin-bottom:6px;">Scaling Exponent (<a href="https://en.wikipedia.org/wiki/Brooks%27s_law" target="_blank">Brooks's Law</a>)</label>
144 <input type="range" id="calcExp" min="0.3" max="1.0" step="0.05" value="0.7" style="width:100%;accent-color:rgb(71,11,0);">
145 <div style="display:flex;justify-content:space-between;font-size:12px;color:#686868;"><span>0.3 (steep)</span><span id="calcExpVal" style="color:rgb(71,11,0);font-size:16px;font-weight:600;">0.70</span><span>1.0 (linear)</span></div>
146 </div>
147 </div>
148 <div style="background:rgba(71,11,0,0.05);border-radius:8px;padding:16px;margin-bottom:20px;border:1px solid rgba(71,11,0,0.15);">
149 <div style="display:flex;align-items:center;gap:12px;margin-bottom:8px;">
150 <label style="color:#666;font-size:13px;font-weight:500;">Model stalled features as unstalled:</label>
151 <label style="display:flex;align-items:center;gap:6px;cursor:pointer;">
152 <input type="radio" name="unstall" id="unstallNone" value="none" style="accent-color:rgb(71,11,0);"> <span style="color:#1d1d1d;font-size:13px;">Off</span>
153 </label>
154 <label style="display:flex;align-items:center;gap:6px;cursor:pointer;">
155 <input type="radio" name="unstall" id="unstallNear" value="near" style="accent-color:rgb(71,11,0);"> <span style="color:#1d1d1d;font-size:13px;">Near-complete only (80%+)</span>
156 </label>
157 <label style="display:flex;align-items:center;gap:6px;cursor:pointer;">
158 <input type="radio" name="unstall" id="unstallAll" value="all" checked style="accent-color:rgb(71,11,0);"> <span style="color:#1d1d1d;font-size:13px;">All stalled</span>
159 </label>
160 </div>
161 <div style="display:flex;align-items:center;gap:16px;">
162 <label style="color:#686868;font-size:12px;">Assumed velocity for unstalled:</label>
163 <select id="unstallSpeed" style="background:#fff;color:#1d1d1d;border:1px solid rgba(71,11,0,0.2);border-radius:4px;padding:4px 8px;font-size:12px;">
164 <option value="p25">Conservative (25th pctl: 0.94pp/q)</option>
165 <option value="median" selected>Median active (2.41pp/q)</option>
166 <option value="p75">Optimistic (75th pctl: 5.16pp/q)</option>
167 </select>
168 </div>
169 <div id="unstallImpact" style="margin-top:8px;font-size:12px;color:#686868;"></div>
170 </div>
171 <div style="font-size:12px;color:#686868;margin-bottom:12px;padding:0 4px;"><strong style="color:#666;">Static milestones</strong> below are against today's 439 measurable features. <strong style="color:rgb(71,11,0);">Moving-target milestones</strong> account for the growing BWA set (~52 new features/year).</div>
172 <div id="calcResults" style="display:grid;grid-template-columns:repeat(auto-fit,minmax(200px,1fr));gap:16px;margin-bottom:12px;"></div>
173 <h4 style="color:rgb(71,11,0);font-size:13px;margin-bottom:8px;">Moving Target: BWA grows ~52 features/year — projected 749 BWA by 2029</h4>
174 <div id="calcMovingResults" style="display:grid;grid-template-columns:repeat(auto-fit,minmax(280px,1fr));gap:16px;margin-bottom:20px;"></div>
175 <div style="display:grid;grid-template-columns:1fr 1fr;gap:20px;">
176 <div class="chart-container"><canvas id="calcTimeline"></canvas></div>
177 <div class="chart-container"><canvas id="calcCost"></canvas></div>
178 </div>
179</div>
180</div>
181
182<div class="grid">
183<div class="card full">
184 <h3>3-Year Strategic Sprint Planner</h3>
185 <p style="font-size:13px;color:#666;margin-bottom:16px;">Set a BWA readiness target and time horizon. The calculator derives the required FTE, then lets you offset paid headcount with community contributions and CX investment.</p>
186
187 <div style="display:flex;gap:40px;flex-wrap:wrap;margin-bottom:20px;">
188 <div style="flex:1;min-width:260px;">
189 <label style="display:block;color:#666;font-size:13px;margin-bottom:6px;">BWA Readiness Target (%)</label>
190 <input type="range" id="sprintTarget" min="30" max="100" value="60" style="width:100%;accent-color:rgb(71,11,0);">
191 <div style="display:flex;justify-content:space-between;font-size:12px;color:#686868;"><span>30%</span><span id="sprintTargetVal" style="color:rgb(71,11,0);font-size:16px;font-weight:600;">60%</span><span>100%</span></div>
192 </div>
193 <div style="flex:1;min-width:260px;">
194 <label style="display:block;color:#666;font-size:13px;margin-bottom:6px;">Time Horizon (years)</label>
195 <input type="range" id="sprintYears" min="1" max="7" value="3" style="width:100%;accent-color:rgb(71,11,0);">
196 <div style="display:flex;justify-content:space-between;font-size:12px;color:#686868;"><span>1yr</span><span id="sprintYearsVal" style="color:rgb(71,11,0);font-size:16px;font-weight:600;">3 years</span><span>7yr</span></div>
197 </div>
198 <div style="flex:1;min-width:260px;">
199 <label style="display:block;color:#666;font-size:13px;margin-bottom:6px;">Avg Annual Salary (EUR)</label>
200 <input type="range" id="sprintSalary" min="50000" max="400000" step="10000" value="200000" style="width:100%;accent-color:rgb(71,11,0);">
201 <div style="display:flex;justify-content:space-between;font-size:12px;color:#686868;"><span>€50k</span><span id="sprintSalaryVal" style="color:rgb(71,11,0);font-size:16px;font-weight:600;">€200k</span><span>€400k</span></div>
202 </div>
203 </div>
204
205 <div style="display:flex;gap:40px;flex-wrap:wrap;margin-bottom:20px;">
206 <div style="flex:1;min-width:260px;">
207 <label style="display:block;color:#666;font-size:13px;margin-bottom:6px;">Community Contribution (% of FTE offset)</label>
208 <input type="range" id="sprintCommunity" min="0" max="50" value="0" style="width:100%;accent-color:rgb(71,11,0);">
209 <div style="display:flex;justify-content:space-between;font-size:12px;color:#686868;"><span>0%</span><span id="sprintCommunityVal" style="color:rgb(71,11,0);font-size:16px;font-weight:600;">0%</span><span>50%</span></div>
210 <div style="font-size:11px;color:#686868;margin-top:4px;">Assumes a portion of required FTE comes from unpaid community contributors, reducing paid headcount.</div>
211 </div>
212 <div style="flex:1;min-width:260px;">
213 <label style="display:block;color:#666;font-size:13px;margin-bottom:6px;">CX Investment (DevRel & Community)</label>
214 <select id="sprintCX" style="width:100%;background:#fff;color:#1d1d1d;border:1px solid rgba(71,11,0,0.2);border-radius:4px;padding:8px;font-size:13px;">
215 <option value="0">None — no community investment</option>
216 <option value="1">Light — 1 DevRel (€130k/yr)</option>
217 <option value="2" selected>Standard — 1 DevRel + 1 Community Mgr (€250k/yr)</option>
218 <option value="3">Full — 2 DevRel + 1 Community Mgr + events budget (€430k/yr)</option>
219 </select>
220 <div style="font-size:11px;color:#686868;margin-top:4px;">CX hires drive community engagement, enabling the contribution offset above. Higher CX investment makes higher community % realistic.</div>
221 </div>
222 <div style="flex:1;min-width:260px;">
223 <label style="display:block;color:#666;font-size:13px;margin-bottom:6px;">Scaling Exponent (<a href="https://en.wikipedia.org/wiki/Brooks%27s_law" target="_blank">Brooks’s Law</a>)</label>
224 <input type="range" id="sprintExp" min="0.3" max="1.0" step="0.05" value="0.7" style="width:100%;accent-color:rgb(71,11,0);">
225 <div style="display:flex;justify-content:space-between;font-size:12px;color:#686868;"><span>0.3 (steep)</span><span id="sprintExpVal" style="color:rgb(71,11,0);font-size:16px;font-weight:600;">0.70</span><span>1.0 (linear)</span></div>
226 </div>
227 </div>
228
229 <div id="sprintResults" style="display:grid;grid-template-columns:repeat(auto-fit,minmax(180px,1fr));gap:16px;margin-bottom:20px;"></div>
230
231 <div id="sprintBreakdown" style="margin-bottom:20px;"></div>
232
233 <div style="display:grid;grid-template-columns:1fr 1fr;gap:20px;">
234 <div class="chart-container"><canvas id="sprintTimeline"></canvas></div>
235 <div class="chart-container"><canvas id="sprintCostChart"></canvas></div>
236 </div>
237</div>
238</div>
239
240<h2>Key Insights</h2>
241<details class="insight">
242 <summary><strong>79 regressions are the #1 problem</strong> <span>— features went backward, some by 50–75 percentage points. Fixing regressions is cheaper than new implementation.</span></summary>
243 <div class="insight-body">
244 <div class="cols">
245 <div>
246 <p style="margin-bottom:8px;">Total regression magnitude across all 51 features: <strong style="color:#a33">1047 percentage points</strong> of lost progress.</p>
247 <p style="margin-bottom:8px;"><strong>Regressions by platform area:</strong></p>
248 <table>
249 <tr><th>Area</th><th>Count</th><th>Avg Regression</th></tr>
250 <tr><td>webassembly</td><td>4</td><td style="color:#a33">-29.7pp</td></tr>
251 <tr><td>html</td><td>4</td><td style="color:#a33">-25.6pp</td></tr>
252 <tr><td>api</td><td>23</td><td style="color:#a33">-19.3pp</td></tr>
253 <tr><td>css</td><td>20</td><td style="color:#a33">-19.1pp</td></tr>
254 </table>
255 </div>
256 <div>
257 <p style="margin-bottom:8px;"><strong>Worst 15 regressions:</strong></p>
258 <table>
259 <tr><th>Feature</th><th>Was</th><th>Now</th><th>Delta</th></tr>
260 <tr><td>base64encodedecode</td><td>100%</td><td>25%</td><td style="color:#a33">-75.0pp</td></tr>
261 <tr><td>object-fit</td><td>97%</td><td>26%</td><td style="color:#a33">-70.9pp</td></tr>
262 <tr><td>webvtt</td><td>63%</td><td>6%</td><td style="color:#a33">-56.4pp</td></tr>
263 <tr><td>empty</td><td>100%</td><td>50%</td><td style="color:#a33">-50.0pp</td></tr>
264 <tr><td>input-submit</td><td>100%</td><td>50%</td><td style="color:#a33">-50.0pp</td></tr>
265 <tr><td>supports-compat</td><td>100%</td><td>50%</td><td style="color:#a33">-50.0pp</td></tr>
266 <tr><td>wasm-multi-value</td><td>67%</td><td>22%</td><td style="color:#a33">-44.4pp</td></tr>
267 <tr><td>wasm-exception-handling</td><td>54%</td><td>21%</td><td style="color:#a33">-33.1pp</td></tr>
268 <tr><td>console</td><td>55%</td><td>23%</td><td style="color:#a33">-32.0pp</td></tr>
269 <tr><td>before-after</td><td>100%</td><td>69%</td><td style="color:#a33">-30.6pp</td></tr>
270 <tr><td>svg</td><td>54%</td><td>24%</td><td style="color:#a33">-29.9pp</td></tr>
271 <tr><td>tab-size</td><td>33%</td><td>5%</td><td style="color:#a33">-28.8pp</td></tr>
272 <tr><td>input-checkbox</td><td>80%</td><td>52%</td><td style="color:#a33">-27.9pp</td></tr>
273 <tr><td>figure</td><td>100%</td><td>75%</td><td style="color:#a33">-25.0pp</td></tr>
274 <tr><td>wasm</td><td>45%</td><td>22%</td><td style="color:#a33">-23.6pp</td></tr>
275 </table>
276 </div>
277 </div>
278 <p style="margin-top:8px;color:#666;">Regressions often indicate code removals, refactors that broke existing functionality, or dependency changes. These are typically cheaper to fix than building new features from scratch — the code existed once and often just needs targeted repairs.</p>
279 </div>
280</details>
281
282<details class="insight">
283 <summary><strong>80 features at 80-95%</strong> <span>are near-complete. The 20 that are stalled represent the highest-ROI targets.</span></summary>
284 <div class="insight-body">
285 <div class="cols">
286 <div>
287 <p style="margin-bottom:8px;"><strong style="color:#1f6e1f">60 actively improving</strong> — on track to reach 95%:</p>
288 <table>
289 <tr><th>Feature</th><th>Score</th><th>Velocity</th></tr>
290 <tr><td>vertical-align</td><td>94.8%</td><td style="color:#1f6e1f">+3.30pp/q</td></tr>
291 <tr><td>font-size</td><td>94.6%</td><td style="color:#1f6e1f">+0.57pp/q</td></tr>
292 <tr><td>constraint-validation</td><td>94.4%</td><td style="color:#1f6e1f">+0.21pp/q</td></tr>
293 <tr><td>trig-functions</td><td>94.3%</td><td style="color:#1f6e1f">+6.10pp/q</td></tr>
294 <tr><td>url</td><td>94.1%</td><td style="color:#1f6e1f">+0.37pp/q</td></tr>
295 <tr><td>textarea</td><td>93.3%</td><td style="color:#1f6e1f">+2.01pp/q</td></tr>
296 <tr><td>webgl</td><td>93.0%</td><td style="color:#1f6e1f">+1.32pp/q</td></tr>
297 <tr><td>oklab</td><td>92.9%</td><td style="color:#1f6e1f">+9.29pp/q</td></tr>
298 <tr><td>calc</td><td>92.6%</td><td style="color:#1f6e1f">+1.05pp/q</td></tr>
299 <tr><td>localstorage</td><td>91.7%</td><td style="color:#1f6e1f">+0.11pp/q</td></tr>
300 <tr><td>import</td><td>91.7%</td><td style="color:#1f6e1f">+0.29pp/q</td></tr>
301 <tr><td>text-encoding</td><td>91.2%</td><td style="color:#1f6e1f">+1.00pp/q</td></tr>
302 <tr><td colspan="3" style="color:#686868">...and 48 more</td></tr>
303 </table>
304 </div>
305 <div>
306 <p style="margin-bottom:8px;"><strong style="color:#8a5a00">20 stalled</strong> — so close yet stuck:</p>
307 <table>
308 <tr><th>Feature</th><th>Score</th></tr>
309 <tr><td>min-max-clamp</td><td>93.0%</td></tr>
310 <tr><td>supports</td><td>92.7%</td></tr>
311 <tr><td>unset-value</td><td>91.7%</td></tr>
312 <tr><td>dataset</td><td>91.1%</td></tr>
313 <tr><td>background-clip</td><td>90.3%</td></tr>
314 <tr><td>not</td><td>90.2%</td></tr>
315 <tr><td>css-escape</td><td>90.0%</td></tr>
316 <tr><td>css-supports</td><td>88.0%</td></tr>
317 <tr><td>dirname</td><td>87.5%</td></tr>
318 <tr><td>input-date-time</td><td>86.4%</td></tr>
319 <tr><td>channel-messaging</td><td>84.0%</td></tr>
320 <tr><td>list-elements</td><td>83.9%</td></tr>
321 <tr><td>currentcolor</td><td>83.3%</td></tr>
322 <tr><td>min-max-width-height</td><td>83.3%</td></tr>
323 <tr><td>prefers-color-scheme</td><td>83.3%</td></tr>
324 <tr><td>shadow-parts</td><td>82.0%</td></tr>
325 <tr><td>gradients</td><td>81.5%</td></tr>
326 <tr><td>border-radius</td><td>80.3%</td></tr>
327 <tr><td>base</td><td>80.3%</td></tr>
328 <tr><td>font-weight</td><td>80.2%</td></tr>
329 </table>
330 </div>
331 </div>
332 <p style="margin-top:8px;color:#666;">Near-complete features need only a small number of failing subtests fixed to cross the 95% threshold. The stalled ones are the highest-ROI investment: small effort, large impact on the headline readiness number.</p>
333 </div>
334</details>
335
336<details class="insight">
337 <summary><strong>Velocity is accelerating</strong> <span>— WPT score doubled from 30% to 62% in 2.5 years. ~13 FTE-equivalent from 115 authors.</span></summary>
338 <div class="insight-body">
339 <div class="cols">
340 <div>
341 <p style="margin-bottom:8px;"><strong>Quarterly progress:</strong></p>
342 <table>
343 <tr><th>Quarter</th><th>Features Improved</th><th>Regressed</th><th>Crossed 95%</th></tr>
344 <tr><td>2024-Q1</td><td style="color:#1f6e1f">93</td><td style="color:#a33">48</td><td style="color:rgb(71,11,0)">7</td></tr>
345 <tr><td>2024-Q3</td><td style="color:#1f6e1f">112</td><td style="color:#a33">53</td><td style="color:rgb(71,11,0)">14</td></tr>
346 <tr><td>2025-Q1</td><td style="color:#1f6e1f">110</td><td style="color:#a33">60</td><td style="color:rgb(71,11,0)">13</td></tr>
347 <tr><td>2025-Q3</td><td style="color:#1f6e1f">127</td><td style="color:#a33">41</td><td style="color:rgb(71,11,0)">12</td></tr>
348 <tr><td>2026-Q1</td><td style="color:#1f6e1f">153</td><td style="color:#a33">47</td><td style="color:rgb(71,11,0)">13</td></tr>
349 </table>
350 </div>
351 <div>
352 <p style="margin-bottom:8px;"><strong>Score distribution shift:</strong></p>
353 <table>
354 <tr><th>Bucket</th><th>2023-Q3</th><th>2026-Q1</th><th>Change</th></tr>
355 <tr><td><span class="tag" style="background:#a3333;color:#a33">0-20%</span></td><td>113</td><td>64</td><td style="color:#1f6e1f">-49</td></tr>
356 <tr><td><span class="tag" style="background:#8a5a0033;color:#8a5a00">20-50%</span></td><td>103</td><td>86</td><td style="color:#1f6e1f">-17</td></tr>
357 <tr><td><span class="tag" style="background:#daa52033;color:#daa520">50-80%</span></td><td>113</td><td>122</td><td style="color:#a33">+9</td></tr>
358 <tr><td><span class="tag" style="background:#68686833;color:#686868">80-95%</span></td><td>50</td><td>80</td><td style="color:#1f6e1f">+30</td></tr>
359 <tr><td><span class="tag" style="background:#1f6e1f33;color:#1f6e1f">95-100%</span></td><td>47</td><td>87</td><td style="color:#1f6e1f">+40</td></tr>
360 </table>
361 <p style="margin-top:4px;color:#686868;font-size:11px;">No data: 167 → 154</p>
362 </div>
363 </div>
364 <p style="margin-top:8px;color:#666;">The improving trend is driven by growing contributor engagement and focused work on layout (CSS Grid, Flexbox) and DOM APIs. Recent quarters show more features crossing the 95% threshold, indicating the project is moving from broad partial support to deep per-feature completion.</p>
365 </div>
366</details>
367
368<details class="insight">
369 <summary><strong>141 stalled features block 75%+ readiness</strong> <span>regardless of investment. Strategic focus matters more than headcount.</span></summary>
370 <div class="insight-body">
371 <div class="cols">
372 <div>
373 <p style="margin-bottom:8px;"><strong>Stalled features by area:</strong></p>
374 <table>
375 <tr><th>Area</th><th>Count</th><th>% of Stalled</th></tr>
376 <tr><td>api</td><td>68</td><td>48%</td></tr>
377 <tr><td>css</td><td>58</td><td>41%</td></tr>
378 <tr><td>html</td><td>7</td><td>5%</td></tr>
379 <tr><td>webassembly</td><td>5</td><td>4%</td></tr>
380 <tr><td>unknown</td><td>2</td><td>1%</td></tr>
381 <tr><td>http</td><td>1</td><td>1%</td></tr>
382 </table>
383 </div>
384 <div>
385 <p style="margin-bottom:8px;"><strong>Highest-scoring stalled features</strong> (closest to completion):</p>
386 <table>
387 <tr><th>Feature</th><th>Score</th><th>Area</th></tr>
388 <tr><td>min-max-clamp</td><td>93.0%</td><td>css</td></tr>
389 <tr><td>supports</td><td>92.7%</td><td>api</td></tr>
390 <tr><td>unset-value</td><td>91.7%</td><td>css</td></tr>
391 <tr><td>dataset</td><td>91.1%</td><td>api</td></tr>
392 <tr><td>background-clip</td><td>90.3%</td><td>css</td></tr>
393 <tr><td>not</td><td>90.2%</td><td>css</td></tr>
394 <tr><td>css-escape</td><td>90.0%</td><td>api</td></tr>
395 <tr><td>css-supports</td><td>88.0%</td><td>api</td></tr>
396 <tr><td>dirname</td><td>87.5%</td><td>api</td></tr>
397 <tr><td>input-date-time</td><td>86.4%</td><td>api</td></tr>
398 <tr><td>channel-messaging</td><td>84.0%</td><td>api</td></tr>
399 <tr><td>list-elements</td><td>83.9%</td><td>api</td></tr>
400 <tr><td>currentcolor</td><td>83.3%</td><td>css</td></tr>
401 <tr><td>min-max-width-height</td><td>83.3%</td><td>css</td></tr>
402 <tr><td>prefers-color-scheme</td><td>83.3%</td><td>css</td></tr>
403 <tr><td colspan="3" style="color:#686868">...and 126 more</td></tr>
404 </table>
405 </div>
406 </div>
407 <p style="margin-top:8px;color:#666;">Stalled features have zero or negative velocity over the entire 2.5-year measurement period. Adding more contributors to <em>already-improving</em> features won't help here — these need dedicated attention, possibly architectural work or new subsystem implementations. Unblocking even 20-30 of the highest-scoring stalled features would significantly shift the projection curves.</p>
408 </div>
409</details>
410
411<details class="insight">
412 <summary><strong>154 features (26%) have no WPT data</strong> <span>— 78 JS built-ins, 23 semantic HTML elements, and 53 other features lack WPT test mapping.</span></summary>
413 <div class="insight-body">
414 <div class="cols">
415 <div>
416 <p style="margin-bottom:8px;"><strong>No-data features by category:</strong></p>
417 <table>
418 <tr><th>Category</th><th>Count</th><th>Likely supported?</th></tr>
419 <tr><td>JS built-ins (SpiderMonkey)</td><td>78</td><td style="font-size:11px;color:#666;">Yes — tested by test262</td></tr>
420 <tr><td>Semantic HTML elements</td><td>23</td><td style="font-size:11px;color:#666;">Yes — trivial elements</td></tr>
421 <tr><td>WebGL extensions</td><td>20</td><td style="font-size:11px;color:#666;">Depends on GPU driver</td></tr>
422 <tr><td>Basic DOM interfaces</td><td>11</td><td style="font-size:11px;color:#666;">Likely</td></tr>
423 <tr><td>DOM APIs</td><td>8</td><td style="font-size:11px;color:#666;">Varies</td></tr>
424 <tr><td>CSS features</td><td>6</td><td style="font-size:11px;color:#666;">Varies</td></tr>
425 <tr><td>WebAssembly features</td><td>3</td><td style="font-size:11px;color:#666;">Likely</td></tr>
426 <tr><td>HTTP features</td><td>3</td><td style="font-size:11px;color:#666;">Varies</td></tr>
427 <tr><td>Other (media types, etc.)</td><td>2</td><td style="font-size:11px;color:#666;">Varies</td></tr>
428 </table>
429 </div>
430 <div>
431 <p style="margin-bottom:8px;"><strong>Why no data?</strong></p>
432 <ul style="margin-left:16px;color:#666;">
433 <li>The WPT Feature Manifest doesn't map these features to WPT test paths</li>
434 <li><strong>78 JS built-ins</strong> (Array, Promise, Intl, etc.) are tested by TC39/test262, not WPT. Servo inherits full support via SpiderMonkey</li>
435 <li><strong>23 semantic HTML elements</strong> (<article>, <nav>, <mark>, etc.) have no special behavior to test — any HTML parser supports them</li>
436 <li><strong>20 WebGL extensions</strong> depend on GPU driver support, not engine code</li>
437 <li>The remaining 33 features are basic DOM, CSS, HTTP, and WebAssembly features with varying support</li>
438 </ul>
439 </div>
440 </div>
441 </div>
442</details>
443
444<details class="insight">
445 <summary><strong>98 features (22%) have web usage data</strong> <span>— from HTTP Archive page scans and Chrome usage metrics.</span></summary>
446 <div class="insight-body">
447 <div class="cols">
448 <div>
449 <p style="margin-bottom:8px;"><strong>Usage distribution:</strong></p>
450 <table>
451 <tr><th>Usage tier</th><th>Count</th><th>Examples</th></tr>
452 <tr><td>>50%</td><td id="usageTierHigh">-</td><td style="font-size:11px;color:#666;" id="usageTierHighEx"></td></tr>
453 <tr><td>10–50%</td><td id="usageTierMed">-</td><td style="font-size:11px;color:#666;" id="usageTierMedEx"></td></tr>
454 <tr><td>1–10%</td><td id="usageTierLow">-</td><td style="font-size:11px;color:#666;" id="usageTierLowEx"></td></tr>
455 <tr><td><1%</td><td id="usageTierTiny">-</td><td style="font-size:11px;color:#666;" id="usageTierTinyEx"></td></tr>
456 </table>
457 </div>
458 <div>
459 <p style="margin-bottom:8px;"><strong>What this means</strong></p>
460 <ul style="margin-left:16px;color:#666;">
461 <li>Usage data comes from HTTP Archive (CSS/HTML page scans across ~8M sites) and Chrome use counters</li>
462 <li>High-usage features that Servo doesn't yet support well represent the biggest gaps in real-world web compatibility</li>
463 <li>The sprint planner uses usage data to prioritize: fixing a 50%-usage feature benefits more users than a 0.01%-usage one</li>
464 <li>Point sizes in the scatter chart scale with usage — larger dots = more widely used on the web</li>
465 </ul>
466 </div>
467 </div>
468 </div>
469</details>
470
471<h2 style="margin-top:32px;">Methodology</h2>
472<div class="card full" style="margin-top:12px;margin-bottom:32px;font-size:14px;line-height:1.7;color:#1d1d1d;">
473 <h3>Data Sources</h3>
474 <p style="margin-bottom:12px;"><strong style="color:rgb(71,11,0);">Web Features</strong> — The <a href="https://github.com/nicolo-ribaudo/tc39-proposal-grouped-features" style="color:rgb(71,11,0);">web-features</a> package defines 1,129 curated feature groups that map to Browser Compat Data (BCD) keys. Each feature has a Baseline status: <em>Widely Available</em> (high) means the feature has been supported across all core browsers for 30+ months. This analysis focuses on the 593 Widely Available features as the target set.</p>
475 <p style="margin-bottom:12px;"><strong style="color:rgb(71,11,0);">WPT Feature Manifest</strong> — The Web Platform Tests project maintains <code style="color:rgb(71,11,0);">WEB_FEATURES_MANIFEST.json</code>, which maps 841 web-feature IDs to 53,549 WPT test paths. This is the critical bridge from feature definitions to measurable test outcomes.</p>
476 <p style="margin-bottom:12px;"><strong style="color:rgb(71,11,0);">WPT Results</strong> — Servo runs the full WPT suite daily on <a href="https://wpt.fyi" style="color:rgb(71,11,0);">wpt.fyi</a>. We use the summary_v2.json format, which records per-test status and subtest counts. Historical snapshots at 6 quarterly intervals (2023-Q3 through 2026-Q1) provide the longitudinal data.</p>
477 <p style="margin-bottom:12px;"><strong style="color:rgb(71,11,0);">Web Usage Data</strong> — Real-world feature usage comes from two sources: <em>HTTP Archive</em> page scans (CSS property/HTML element detection across ~8M sites via BigQuery, February 2026 crawl) and <em>Chrome use counters</em> (day_percentage from chromestatus.com popularity data). HTTP Archive data is preferred when both sources cover a feature. Of the 439 measurable BWA features, 98 (22%) have usage data — 52 from HTTP Archive and 46 from Chrome counters only. Usage is shown as point sizes in the scatter chart and as a "usage-weighted readiness" metric in the sprint planner.</p>
478
479 <h3 style="margin-top:20px;">Scoring Model</h3>
480 <p style="margin-bottom:12px;">Each feature's score is the average per-test pass rate across all matched WPT tests. For tests with subtests, the score is <code style="color:rgb(71,11,0);">passed_subtests / total_subtests</code>. For simple pass/fail tests, the score is 0 or 1. A feature is considered <strong style="color:#1f6e1f;">fully supported</strong> at ≥95% score.</p>
481 <p style="margin-bottom:12px;">Features with no WPT manifest mapping (154 of 593) are categorized as “No Data.” These break down into 78 JS built-ins (supported via SpiderMonkey, tested by test262 not WPT), 23 semantic HTML elements (trivial — no special behavior to test), 20 WebGL extensions (GPU-driver-dependent), and 33 other features (basic DOM, CSS, HTTP, WebAssembly). The 78 JS built-ins and 23 semantic HTML elements are supported via SpiderMonkey and the HTML parser respectively; the 20 WebGL extensions depend on GPU driver support; the remaining 33 have unknown status.</p>
482
483 <h3 style="margin-top:20px;">FTE-Equivalent Contributors</h3>
484 <p style="margin-bottom:12px;">The contributor count uses <strong style="color:rgb(71,11,0);">full-time equivalents (FTE)</strong>, not raw headcount. Computed from per-author commit counts over Jul 2025 – Jan 2026 (7 months), excluding bots (dependabot, WPT Sync). Each author's FTE fraction = <code style="color:rgb(71,11,0);">min(their_commits / 154, 1.0)</code>, where 154 = 22 commits/month × 7 months (~1 commit per working day). The sum across all 115 human authors yields <strong style="color:rgb(71,11,0);">~13 FTE</strong>. Of these, 9 core contributors operate at ≥50% FTE, with a long tail of occasional contributors. This FTE figure is what drives the projection and cost models — it represents the effective engineering capacity, which is what matters for funding decisions.</p>
485
486 <h3 style="margin-top:20px;">Velocity & Projections</h3>
487 <p style="margin-bottom:12px;">Per-feature velocity is computed as the improvement per quarter from 2023-Q3 to present. We use <code style="color:rgb(71,11,0);">max(overall_velocity, recent_velocity)</code> where recent velocity covers the last 4 quarters, to account for accelerating progress. Features with velocity ≤0.001 percentage points/quarter are classified as <strong style="color:#8a5a00;">stalled</strong>.</p>
488 <p style="margin-bottom:12px;">Projections extrapolate each feature individually: <code style="color:rgb(71,11,0);">quarters_to_95% = (0.95 - current_score) / (velocity × scale_factor)</code>. The scale factor models additional FTEs using a sublinear power law: <code style="color:rgb(71,11,0);">scale = (new_fte / current_fte)<sup>exponent</sup></code>. The default exponent of 0.7 reflects <a href="https://en.wikipedia.org/wiki/Brooks%27s_law" target="_blank" style="color:rgb(71,11,0);">Brooks's Law</a> — communication overhead means doubling contributors doesn't double output.</p>
489
490 <h3 style="margin-top:20px;">Cost Model</h3>
491 <p style="margin-bottom:12px;">Cost is calculated as: <code style="color:rgb(71,11,0);">additional_FTE × salary × years_to_milestone</code>, where the milestone date is determined by the Nth-percentile feature reaching 95%. This represents the <em>marginal</em> cost of accelerating beyond the current trajectory — not the total program cost. The model assumes FTEs can be allocated to stalled features and that the scaling exponent applies uniformly.</p>
492
493 <h3 style="margin-top:20px;">Limitations</h3>
494 <ul style="margin-left:20px;">
495 <li>26% of Widely Available features lack WPT test mapping, creating a coverage gap</li>
496 <li>Servo is not tracked in BCD, so Baseline status cannot directly include Servo</li>
497 <li>WPT test coverage varies by feature — some features have thousands of tests, others have few</li>
498 <li>The sublinear scaling model is a simplification; actual contributor efficiency depends on the nature of the work</li>
499 <li>Projections assume constant velocity — breakout improvements in layout, CSS, or JS engines could cause step-function changes</li>
500 <li>Stalled features may require architectural work rather than incremental test fixes</li>
501 <li>Web usage data covers only 22% of measurable features — HTTP Archive detects CSS/HTML observables but cannot measure JS API usage, and many BCD sub-features map to generic observables (e.g., <code style="color:rgb(71,11,0);">width</code>) that inflate counts</li>
502 </ul>
503</div>
504
505<script>
506Chart.defaults.color = '#666';
507Chart.defaults.borderColor = 'rgba(71,11,0,0.1)';
508Chart.defaults.font.family = '"Pragati Narrow", sans-serif';
509
510// 1. WPT Trajectory
511new Chart(document.getElementById('wptTrajectory'), {
512 type: 'line',
513 data: {
514 labels: ["2023-04-01","2023-07-01","2023-10-01","2024-01-01","2024-04-01","2024-07-01","2024-10-01","2025-01-01","2025-04-01","2025-07-01","2025-10-01","2026-01-01","2026-02-13"],
515 datasets: [{
516 label: 'WPT Pass Rate (%)',
517 data: [30.35,32.04,33.24,34.32,38.38,39.83,42.06,47.36,51.34,55.51,57.03,60.44,62.38],
518 borderColor: 'rgb(71,11,0)',
519 backgroundColor: 'rgba(71,11,0,0.1)',
520 fill: true,
521 tension: 0.3,
522 pointRadius: 4,
523 pointBackgroundColor: 'rgb(71,11,0)',
524 }]
525 },
526 options: {
527 responsive: true, maintainAspectRatio: false,
528 scales: {
529 y: { min: 25, max: 70, ticks: { callback: v => v + '%' } },
530 x: { ticks: { maxTicksLimit: 7 } }
531 },
532 plugins: { legend: { display: false } }
533 }
534});
535
536// 2. Distribution stacked bar
537new Chart(document.getElementById('distribution'), {
538 type: 'bar',
539 data: {
540 labels: ["2023-Q3","2024-Q1","2024-Q3","2025-Q1","2025-Q3","2026-Q1"],
541 datasets: [{"label":"95-100%","data":[47,52,60,71,79,87],"backgroundColor":"#1f6e1f"},{"label":"80-95%","data":[50,45,56,63,66,80],"backgroundColor":"#686868"},{"label":"50-80%","data":[113,124,116,115,126,122],"backgroundColor":"#daa520"},{"label":"20-50%","data":[103,101,93,86,85,86],"backgroundColor":"#8a5a00"},{"label":"0-20%","data":[113,105,106,99,79,64],"backgroundColor":"#a33"}]
542 },
543 options: {
544 responsive: true, maintainAspectRatio: false,
545 scales: { x: { stacked: true }, y: { stacked: true, max: 600 } },
546 plugins: { legend: { position: 'bottom', labels: { boxWidth: 12 } } }
547 }
548});
549
550// 3. By year cumulative
551new Chart(document.getElementById('byYear'), {
552 type: 'bar',
553 data: {
554 labels: ["Through 2018","Through 2019","Through 2020","Through 2021","Through 2022","Through 2023","Through 2024","Through 2025","Through 2026"],
555 datasets: [
556 { label: 'Fully Supported', data: [58,60,61,61,71,73,78,86,86], backgroundColor: '#1f6e1f' },
557 { label: 'Partial', data: [126,144,153,160,209,232,257,284,287], backgroundColor: '#8a5a00' },
558 { label: 'Other', data: [82,100,109,116,150,174,195,216,217], backgroundColor: 'rgba(71,11,0,0.2)' },
559 ]
560 },
561 options: {
562 responsive: true, maintainAspectRatio: false,
563 scales: { x: { stacked: true }, y: { stacked: true } },
564 plugins: { legend: { position: 'bottom', labels: { boxWidth: 12 } } }
565 }
566});
567
568// 4. Commits & contributors
569new Chart(document.getElementById('commits'), {
570 type: 'bar',
571 data: {
572 labels: ["2023-01","2023-02","2023-03","2023-04","2023-05","2023-06","2023-07","2023-08","2023-09","2023-10","2023-11","2023-12","2024-01","2024-02","2024-03","2024-04","2024-05","2024-06","2024-07","2024-08","2024-09","2024-10","2024-11","2024-12","2025-01","2025-02","2025-03","2025-04","2025-05","2025-06","2025-07","2025-08","2025-09","2025-10","2025-11","2025-12","2026-01","2026-02"],
573 datasets: [
574 { label: 'Commits', data: [168,187,197,166,495,279,86,235,151,140,149,110,193,166,323,186,163,157,171,269,217,332,216,216,289,305,317,314,251,350,363,439,341,438,401,340,398,197], backgroundColor: 'rgba(71,11,0,0.5)', yAxisID: 'y' },
575 { label: 'Unique Authors', data: [25,22,22,21,40,27,17,25,15,14,13,12,21,25,34,29,25,24,31,32,26,40,21,29,30,40,59,50,41,45,44,48,42,50,44,52,51,39], type: 'line', borderColor: '#8a5a00', backgroundColor: 'transparent', yAxisID: 'y1', pointRadius: 2, tension: 0.3 },
576 ]
577 },
578 options: {
579 responsive: true, maintainAspectRatio: false,
580 scales: {
581 y: { position: 'left', title: { display: true, text: 'Commits' } },
582 y1: { position: 'right', grid: { drawOnChartArea: false }, title: { display: true, text: 'Authors' } },
583 x: { ticks: { maxTicksLimit: 12 } }
584 },
585 plugins: { legend: { position: 'bottom', labels: { boxWidth: 12 } } }
586 }
587});
588
589// 5. Projections
590new Chart(document.getElementById('projections'), {
591 type: 'line',
592 data: {
593 labels: ["Now","+1y","+2y","+3y","+4y","+5y","+7y","+10y","+15y","+20y"],
594 datasets: [{"label":"Current (13 FTE)","data":[87,146,182,205,219,234,252,272,285,295],"borderColor":"rgb(71,11,0)","backgroundColor":"transparent","tension":0.3,"pointRadius":3},{"label":"2x (26 FTE)","data":[87,171,205,234,248,261,279,288,300,308],"borderColor":"#1f6e1f","backgroundColor":"transparent","tension":0.3,"pointRadius":3},{"label":"3x (39 FTE)","data":[87,183,224,248,266,278,285,298,308,310],"borderColor":"#8a5a00","backgroundColor":"transparent","tension":0.3,"pointRadius":3},{"label":"5x (65 FTE)","data":[87,205,248,269,281,288,298,307,313,316],"borderColor":"#a33","backgroundColor":"transparent","tension":0.3,"pointRadius":3}]
595 },
596 options: {
597 responsive: true, maintainAspectRatio: false,
598 scales: {
599 y: { min: 0, max: 400, title: { display: true, text: 'Features >= 95%' } },
600 },
601 plugins: {
602 legend: { position: 'bottom', labels: { boxWidth: 12 } },
603 annotation: { annotations: { line1: { type: 'line', yMin: 297, yMax: 297, borderColor: 'rgba(71,11,0,0.3)', borderDash: [5,5], label: { content: '50%', display: true } } } }
604 }
605 }
606});
607
608// 6. Stalled donut
609new Chart(document.getElementById('stalledDonut'), {
610 type: 'doughnut',
611 data: {
612 labels: ["api","css","html","http","unknown","webassembly"],
613 datasets: [{
614 data: [68,58,7,1,2,5],
615 backgroundColor: ['#8b3a3a', '#8a5a00', '#a33', '#1f6e1f', '#666', '#686868', 'rgba(71,11,0,0.3)'],
616 }]
617 },
618 options: {
619 responsive: true, maintainAspectRatio: false,
620 plugins: { legend: { position: 'right', labels: { boxWidth: 12 } } }
621 }
622});
623
624// 7. Regressions horizontal bar
625new Chart(document.getElementById('regressions'), {
626 type: 'bar',
627 data: {
628 labels: ["base64encodedecode","object-fit","webvtt","empty","input-submit","supports-compat","wasm-multi-value","wasm-exception-handling","console","before-after","svg","tab-size","input-checkbox","figure","wasm","input-number","input-radio","change-event","transforms2d","canvas-createconicgradient","wasm-threads","meter","audio-worklet","file-selector-button","min-max-width-height"],
629 datasets: [
630 { label: 'Was (2023-Q3)', data: [100,96.8,62.9,100,100,100,66.7,53.8,55.1,100,54,33.3,80,100,45.2,75,75,50,85.9,18.2,22.2,51,33.5,66.7,100], backgroundColor: 'rgba(71,11,0,0.3)', borderColor: 'rgb(71,11,0)', borderWidth: 1 },
631 { label: 'Now (2026-Q1)', data: [25,25.9,6.4,50,50,50,22.2,20.7,23.1,69.4,24.1,4.5,52.1,75,21.6,53.6,53.8,29.5,66.7,0,4.4,33.3,16.3,50,83.3], backgroundColor: 'rgba(204,68,68,0.5)', borderColor: '#a33', borderWidth: 1 },
632 ]
633 },
634 options: {
635 indexAxis: 'y',
636 responsive: true, maintainAspectRatio: false,
637 scales: { x: { min: 0, max: 100, ticks: { callback: v => v + '%' } } },
638 plugins: { legend: { position: 'bottom', labels: { boxWidth: 12 } } }
639 }
640});
641
642// 8. Feature scatter
643const areaColors = { api: '#8b3a3a', css: '#8a5a00', html: '#a33', javascript: '#1f6e1f', webassembly: '#666', svg: '#686868', http: 'rgba(71,11,0,0.4)', unknown: 'rgba(71,11,0,0.2)' };
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646const areas = [...new Set(scatterData.map(d => d.area))];
647new Chart(document.getElementById('scatter'), {
648 type: 'scatter',
649 data: {
650 datasets: areas.map(area => ({
651 label: area,
652 data: scatterData.filter(d => d.area === area).map(d => ({ x: d.score * 100, y: d.velocity * 100, name: d.name, usage: d.usage })),
653 backgroundColor: areaColors[area] || 'rgba(71,11,0,0.2)',
654 pointRadius: ctx => {
655 const u = ctx.raw?.usage;
656 return u != null ? Math.max(3, Math.sqrt(u * 100) * 2) : 3;
657 },
658 pointHoverRadius: 8,
659 }))
660 },
661 options: {
662 responsive: true, maintainAspectRatio: false,
663 scales: {
664 x: { min: 0, max: 100, title: { display: true, text: 'Current Score (%)' }, ticks: { callback: v => v + '%' } },
665 y: { title: { display: true, text: 'Velocity (pp/quarter)' }, ticks: { callback: v => v.toFixed(1) + 'pp' } },
666 },
667 plugins: {
668 legend: { position: 'bottom', labels: { boxWidth: 12 } },
669 tooltip: {
670 callbacks: {
671 label: ctx => {
672 let s = ctx.raw.name + ': ' + ctx.raw.x.toFixed(1) + '% score, ' + ctx.raw.y.toFixed(2) + 'pp/q velocity';
673 if (ctx.raw.usage != null) s += ', ' + (ctx.raw.usage * 100).toFixed(1) + '% web usage';
674 return s;
675 }
676 }
677 }
678 }
679 }
680});
681
682// Populate usage tier insight table
683{
684 const entries = Object.entries(webUsageMap).sort((a, b) => b[1] - a[1]);
685 const tiers = [
686 { id: 'High', test: v => v > 0.5 },
687 { id: 'Med', test: v => v >= 0.1 && v <= 0.5 },
688 { id: 'Low', test: v => v >= 0.01 && v < 0.1 },
689 { id: 'Tiny', test: v => v < 0.01 },
690 ];
691 for (const t of tiers) {
692 const feats = entries.filter(([, v]) => t.test(v));
693 const el = document.getElementById('usageTier' + t.id);
694 const exEl = document.getElementById('usageTier' + t.id + 'Ex');
695 if (el) el.textContent = feats.length;
696 if (exEl) exEl.textContent = feats.slice(0, 5).map(([n]) => n).join(', ') + (feats.length > 5 ? ', ...' : '');
697 }
698}
699
700// ============================================================
701// Moving Target Chart
702// ============================================================
703{
704 const mtFeatures = 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705 const mtMedianV = 0.02412099133410609;
706 const mtCurrentC = 13;
707 const mtExp = 0.7;
708 const mtYears = [0, 1, 2, 3, 4, 5, 7, 10, 15];
709 const mtScenarios = [
710 { label: 'Current (13 FTE)', fte: 13, color: 'rgb(71,11,0)' },
711 { label: '45 FTE', fte: 45, color: '#1f6e1f' },
712 { label: '65 FTE', fte: 65, color: '#8a5a00' },
713 { label: '150 FTE', fte: 150, color: '#a33' },
714 ];
715
716 // BWA count at each year point
717 const mtBWACounts = mtYears.map(y => {
718 const q = y * 4;
719 return mtFeatures.filter(f => f.entryQ <= q).length;
720 });
721
722 const mtDatasets = [
723 {
724 label: 'BWA Target (growing)',
725 data: mtBWACounts,
726 borderColor: 'rgba(71,11,0,0.3)',
727 backgroundColor: 'transparent',
728 borderDash: [5, 5],
729 tension: 0.3,
730 pointRadius: 3,
731 },
732 ...mtScenarios.map(sc => {
733 const scale = Math.pow(sc.fte / mtCurrentC, mtExp);
734 const data = mtYears.map(y => {
735 const q = y * 4;
736 const activeFeatures = mtFeatures.filter(f => f.entryQ <= q);
737 let passing = 0;
738 for (const f of activeFeatures) {
739 if (f.score >= 0.95 && f.entryQ === 0) { passing++; continue; }
740 const v = (f.stalled ? mtMedianV : f.velocity) * scale;
741 if (v <= 0.001) continue;
742 const qAvail = Math.max(0, q - f.entryQ);
743 const projected = f.score + v * qAvail;
744 if (projected >= 0.95) passing++;
745 }
746 return passing;
747 });
748 return {
749 label: sc.label,
750 data,
751 borderColor: sc.color,
752 backgroundColor: 'transparent',
753 tension: 0.3,
754 pointRadius: 3,
755 };
756 }),
757 ];
758
759 new Chart(document.getElementById('movingTarget'), {
760 type: 'line',
761 data: {
762 labels: mtYears.map(y => y === 0 ? 'Now' : '+' + y + 'y'),
763 datasets: mtDatasets,
764 },
765 options: {
766 responsive: true, maintainAspectRatio: false,
767 scales: {
768 y: { min: 0, title: { display: true, text: 'Features' } },
769 },
770 plugins: {
771 legend: { position: 'bottom', labels: { boxWidth: 12 } },
772 },
773 },
774 });
775}
776
777// ============================================================
778// Interactive Projection & Cost Calculator
779// ============================================================
780const featureVData = 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782const currentC = 13;
783const widelyN = 593;
784const measurableN = featureVData.length;
785const unstallVelocities = {
786 p25: 0.00942113961211713,
787 median: 0.02412099133410609,
788 p75: 0.051550438596491235,
789};
790const milestones = [
791 { pct: 25, label: '25%', count: Math.ceil(measurableN * 0.25), color: '#666' },
792 { pct: 50, label: '50%', count: Math.ceil(measurableN * 0.50), color: 'rgb(71,11,0)' },
793 { pct: 75, label: '75%', count: Math.ceil(measurableN * 0.75), color: '#8a5a00' },
794 { pct: 90, label: '90%', count: Math.ceil(measurableN * 0.90), color: '#a33' },
795];
796
797function runCalc() {
798 const contrib = +document.getElementById('calcContrib').value;
799 const salary = +document.getElementById('calcSalary').value;
800 const exp = +document.getElementById('calcExp').value;
801 const unstallMode = document.querySelector('input[name="unstall"]:checked').value;
802 const unstallSpeed = document.getElementById('unstallSpeed').value;
803 document.getElementById('calcContribVal').textContent = contrib;
804 document.getElementById('calcSalaryVal').textContent = '€' + (salary / 1000).toFixed(0) + 'k';
805 document.getElementById('calcExpVal').textContent = exp.toFixed(2);
806
807 const scale = Math.pow(contrib / currentC, exp);
808 const additional = Math.max(0, contrib - currentC);
809 const assignedV = unstallVelocities[unstallSpeed];
810
811 // Count how many features get unstalled
812 let unstalledCount = 0;
813
814 // Compute quarters-to-95% for each feature
815 const qtrs = featureVData.map(f => {
816 if (f.score >= 0.95) return 0;
817 let v = f.velocity;
818 if (f.stalled && unstallMode !== 'none') {
819 const eligible = unstallMode === 'all' || (unstallMode === 'near' && f.score >= 0.80);
820 if (eligible) { v = assignedV; unstalledCount++; }
821 }
822 if (v <= 0.001) return Infinity;
823 return (0.95 - f.score) / (v * scale);
824 });
825
826 // Update unstall impact text
827 const impactEl = document.getElementById('unstallImpact');
828 if (unstallMode === 'none') {
829 impactEl.textContent = '';
830 } else {
831 const totalStalled = featureVData.filter(f => f.stalled).length;
832 impactEl.innerHTML = '<span style="color:rgb(71,11,0);font-weight:700;">' + unstalledCount + ' of ' + totalStalled + ' stalled features</span> modeled with ' + (assignedV * 100).toFixed(2) + 'pp/quarter velocity';
833 }
834
835 // Sort finite values
836 const finite = qtrs.filter(q => isFinite(q)).sort((a, b) => a - b);
837 const stalled = qtrs.filter(q => !isFinite(q)).length;
838 const already = qtrs.filter(q => q === 0).length;
839
840 // Milestone results
841 const results = milestones.map(m => {
842 const idx = m.count - 1;
843 if (idx < finite.length) {
844 const q = finite[idx];
845 const years = q / 4;
846 const date = new Date(2026, 1, 13);
847 date.setMonth(date.getMonth() + Math.round(q * 3));
848 return { ...m, quarters: q, years, date: date.toLocaleDateString('en-US', { year: 'numeric', month: 'short' }), cost: additional * salary * years, reachable: true };
849 }
850 return { ...m, reachable: false, quarters: Infinity, years: Infinity, date: 'Not reachable', cost: Infinity };
851 });
852
853 // Update result cards
854 const resultsDiv = document.getElementById('calcResults');
855 resultsDiv.innerHTML = results.map(r => {
856 const costStr = r.reachable ? '€' + (r.cost / 1e6).toFixed(1) + 'M total' : 'N/A';
857 const costYrStr = r.reachable && r.years > 0 ? '€' + (additional * salary / 1e6).toFixed(1) + 'M/yr' : '';
858 const timeStr = r.reachable ? r.years.toFixed(1) + 'y' : '—';
859 return '<div style="background:rgba(71,11,0,0.05);border-radius:8px;padding:16px;text-align:center;border:1px solid ' + r.color + '33">' +
860 '<div style="font-size:13px;color:' + r.color + '">' + r.label + ' of measurable (' + r.count + '/' + measurableN + ')</div>' +
861 '<div style="font-size:28px;font-weight:700;color:rgb(71,11,0);margin:4px 0">' + timeStr + '</div>' +
862 '<div style="font-size:12px;color:#686868">' + (r.reachable ? 'by ' + r.date : 'Not reachable — stalled features block this milestone') + '</div>' +
863 '<div style="font-size:16px;color:#666;margin-top:4px">' + costStr + '</div>' +
864 (costYrStr ? '<div style="font-size:13px;color:#686868">' + costYrStr + '</div>' : '') +
865 '</div>';
866 }).join('') +
867 '<div style="background:rgba(71,11,0,0.05);border-radius:8px;padding:16px;text-align:center;border:1px solid rgba(71,11,0,0.15)">' +
868 '<div style="font-size:13px;color:#666">Stalled (no velocity)</div>' +
869 '<div style="font-size:28px;font-weight:700;color:#a33">' + stalled + '</div>' +
870 '<div style="font-size:12px;color:#686868">Need strategic intervention</div>' +
871 '</div>';
872
873 // Timeline chart
874 const timelineYears = [0, 0.5, 1, 2, 3, 5, 7, 10, 15, 20];
875 const timelineData = timelineYears.map(y => {
876 const q = y * 4;
877 return finite.filter(fq => fq <= q).length;
878 });
879
880 if (window._calcTimeline) window._calcTimeline.destroy();
881 window._calcTimeline = new Chart(document.getElementById('calcTimeline'), {
882 type: 'line',
883 data: {
884 labels: timelineYears.map(y => y === 0 ? 'Now' : '+' + y + 'y'),
885 datasets: [{
886 label: 'Features >= 95%',
887 data: timelineData,
888 borderColor: 'rgb(71,11,0)',
889 backgroundColor: 'rgba(71,11,0,0.1)',
890 fill: true,
891 tension: 0.3,
892 pointRadius: 4,
893 }]
894 },
895 options: {
896 responsive: true, maintainAspectRatio: false,
897 scales: {
898 y: { min: 0, max: measurableN, title: { display: true, text: 'Features >= 95% (of ' + measurableN + ' measurable)' } },
899 },
900 plugins: {
901 legend: { display: false },
902 title: { display: true, text: 'Projected Feature Completion (' + contrib + ' contributors)', color: '#666' },
903 }
904 }
905 });
906
907 // Cost chart
908 const costData = milestones.filter((_,i) => results[i].reachable).map((_,i) => results[i]);
909 if (window._calcCost) window._calcCost.destroy();
910 window._calcCost = new Chart(document.getElementById('calcCost'), {
911 type: 'bar',
912 data: {
913 labels: costData.map(r => r.label),
914 datasets: [{
915 label: 'Marginal Cost (€M)',
916 data: costData.map(r => +(r.cost / 1e6).toFixed(2)),
917 backgroundColor: costData.map(r => r.color + '99'),
918 borderColor: costData.map(r => r.color),
919 borderWidth: 1,
920 }]
921 },
922 options: {
923 responsive: true, maintainAspectRatio: false,
924 scales: {
925 y: { title: { display: true, text: 'Marginal Cost (€M)' }, ticks: { callback: v => '€' + v + 'M' } },
926 },
927 plugins: {
928 legend: { display: false },
929 title: { display: true, text: 'Cost of Additional Contributors (' + additional + ' new @ €' + (salary/1000).toFixed(0) + 'k)', color: '#666' },
930 }
931 }
932 });
933
934 // Moving-target results
935 const mtMedianV = 0.02412099133410609;
936 const mtTargetYears = [3, 5, 7, 10];
937 const mtResults = mtTargetYears.map(targetY => {
938 const targetQ = targetY * 4;
939 const activeFeats = mtAllFeatures.filter(f => f.entryQ <= targetQ);
940 const bwaCount = activeFeats.length;
941 let passing = 0;
942 for (const f of activeFeats) {
943 if (f.score >= 0.95 && f.entryQ === 0) { passing++; continue; }
944 let v = f.velocity;
945 if (f.stalled && unstallMode !== 'none') {
946 const eligible = unstallMode === 'all' || (unstallMode === 'near' && f.score >= 0.80);
947 if (eligible) v = assignedV;
948 }
949 if (v <= 0.001) v = (unstallMode !== 'none') ? assignedV : 0;
950 if (v <= 0.001) continue;
951 const qAvail = Math.max(0, targetQ - f.entryQ);
952 const projected = f.score + v * scale * qAvail;
953 if (projected >= 0.95) passing++;
954 }
955 const pct = (passing / bwaCount * 100);
956 const date = new Date(2026, 1, 13);
957 date.setFullYear(date.getFullYear() + targetY);
958 return { targetY, bwaCount, passing, pct, date: date.toLocaleDateString('en-US', { year: 'numeric', month: 'short' }) };
959 });
960
961 const mtDiv = document.getElementById('calcMovingResults');
962 mtDiv.innerHTML = mtResults.map(r => {
963 const atTarget = r.pct >= 90;
964 const borderColor = atTarget ? '#1f6e1f' : '#8a5a00';
965 return '<div style="background:rgba(71,11,0,0.05);border-radius:8px;padding:14px;border:1px solid ' + borderColor + '33;display:flex;justify-content:space-between;align-items:center;">' +
966 '<div>' +
967 '<div style="font-size:12px;color:#666;">By ' + r.date + ' (' + r.bwaCount + ' BWA features)</div>' +
968 '<div style="font-size:24px;font-weight:700;color:' + (atTarget ? '#1f6e1f' : 'rgb(71,11,0)') + ';">' + r.pct.toFixed(1) + '%</div>' +
969 '</div>' +
970 '<div style="text-align:right;">' +
971 '<div style="font-size:20px;font-weight:600;color:rgb(71,11,0);">' + r.passing + '<span style="font-size:13px;color:#686868;">/' + r.bwaCount + '</span></div>' +
972 '<div style="font-size:11px;color:#686868;">features at ≥95%</div>' +
973 '</div>' +
974 '</div>';
975 }).join('');
976}
977
978document.getElementById('calcContrib').addEventListener('input', runCalc);
979document.getElementById('calcSalary').addEventListener('input', runCalc);
980document.getElementById('calcExp').addEventListener('input', runCalc);
981document.querySelectorAll('input[name="unstall"]').forEach(el => el.addEventListener('change', runCalc));
982document.getElementById('unstallSpeed').addEventListener('change', runCalc);
983runCalc();
984
985// ============================================================
986// 3-Year Strategic Sprint Planner
987// ============================================================
988{
989 const sprintCurrentFTE = 13;
990 const sprintCurrentPassing = 87; // features at >=95%
991
992 // CX investment cost tiers (annual)
993 const cxCosts = { '0': 0, '1': 130000, '2': 250000, '3': 430000 };
994 const cxLabels = { '0': 'None', '1': '1 DevRel', '2': '1 DevRel + 1 Community Mgr', '3': '2 DevRel + 1 Community Mgr + events' };
995
996 function runSprint() {
997 const targetPct = +document.getElementById('sprintTarget').value;
998 const years = +document.getElementById('sprintYears').value;
999 const salary = +document.getElementById('sprintSalary').value;
1000 const communityPct = +document.getElementById('sprintCommunity').value / 100;
1001 const cxTier = document.getElementById('sprintCX').value;
1002 const exp = +document.getElementById('sprintExp').value;
1003
1004 document.getElementById('sprintTargetVal').textContent = targetPct + '%';
1005 document.getElementById('sprintYearsVal').textContent = years + (years === 1 ? ' year' : ' years');
1006 document.getElementById('sprintSalaryVal').textContent = '\u20AC' + (salary / 1000).toFixed(0) + 'k';
1007 document.getElementById('sprintCommunityVal').textContent = communityPct * 100 + '%';
1008 document.getElementById('sprintExpVal').textContent = exp.toFixed(2);
1009
1010 const targetQ = years * 4;
1011
1012 // Use the moving-target feature data to account for BWA growth
1013 const activeFeats = mtAllFeatures.filter(f => f.entryQ <= targetQ);
1014 const bwaCount = activeFeats.length;
1015 const targetCount = Math.ceil(bwaCount * targetPct / 100);
1016
1017 // Binary search for FTE needed to get targetCount features to 95%
1018 function countPassing(fte) {
1019 const scale = Math.pow(fte / sprintCurrentFTE, exp);
1020 let passing = 0;
1021 for (const f of activeFeats) {
1022 if (f.score >= 0.95 && f.entryQ === 0) { passing++; continue; }
1023 let v = f.velocity;
1024 // Assume stalled features get unstalled with median velocity (same as main calc default)
1025 if (f.stalled) v = 0.02412099133410609;
1026 if (v <= 0.001) continue;
1027 const qAvail = Math.max(0, targetQ - f.entryQ);
1028 const projected = f.score + v * scale * qAvail;
1029 if (projected >= 0.95) passing++;
1030 }
1031 return passing;
1032 }
1033
1034 // Binary search: find min FTE to hit targetCount
1035 let lo = 1, hi = 200, requiredFTE = 200;
1036 while (lo <= hi) {
1037 const mid = Math.floor((lo + hi) / 2);
1038 if (countPassing(mid) >= targetCount) {
1039 requiredFTE = mid;
1040 hi = mid - 1;
1041 } else {
1042 lo = mid + 1;
1043 }
1044 }
1045
1046 // Cap at a reasonable value
1047 const reachable = requiredFTE <= 200;
1048 const totalFTE = requiredFTE;
1049 const communityFTE = Math.round(Math.max(0, totalFTE - sprintCurrentFTE) * communityPct);
1050 const paidNewFTE = Math.max(0, totalFTE - sprintCurrentFTE - communityFTE);
1051 const paidTotalFTE = sprintCurrentFTE + paidNewFTE;
1052 const cxAnnual = cxCosts[cxTier];
1053
1054 const engCostPerYear = paidNewFTE * salary;
1055 const cxCostPerYear = cxAnnual;
1056 const totalCostPerYear = engCostPerYear + cxCostPerYear;
1057 const totalCostSprint = totalCostPerYear * years;
1058
1059 // Also compute what we reach at current pace
1060 const currentPassing = countPassing(sprintCurrentFTE);
1061
1062 // Compute usage-weighted readiness from scatterData (current features with names+usage)
1063 const totalUsage = scatterData.reduce((s, f) => s + (f.usage || 0), 0);
1064 const passingUsage = scatterData.filter(f => f.score >= 0.95).reduce((s, f) => s + (f.usage || 0), 0);
1065 const usageReadiness = totalUsage > 0 ? (passingUsage / totalUsage * 100).toFixed(1) : 'N/A';
1066
1067 // Result cards
1068 const resultsDiv = document.getElementById('sprintResults');
1069 resultsDiv.innerHTML = [
1070 { label: 'BWA Features in ' + years + 'yr', value: bwaCount, sub: 'growing at ~52/yr', color: '#666' },
1071 { label: 'Target (' + targetPct + '%)', value: targetCount, sub: 'features at \u226595%', color: 'rgb(71,11,0)' },
1072 { label: 'Required Total FTE', value: reachable ? totalFTE : '>200', sub: reachable ? (totalFTE - sprintCurrentFTE) + ' new beyond current 13' : 'Not reachable', color: reachable ? 'rgb(71,11,0)' : '#a33' },
1073 { label: 'At Current Pace (13 FTE)', value: currentPassing, sub: (currentPassing / bwaCount * 100).toFixed(1) + '% of ' + bwaCount, color: '#686868' },
1074 { label: 'Usage-Weighted Readiness', value: usageReadiness + '%', sub: 'of web traffic by supported features', color: '#1f6e1f' },
1075 { label: 'Community FTE Offset', value: communityFTE, sub: communityFTE > 0 ? 'saves \u20AC' + ((communityFTE * salary * years) / 1e6).toFixed(1) + 'M over ' + years + 'yr' : 'no community offset', color: communityFTE > 0 ? '#1f6e1f' : '#686868' },
1076 { label: 'Paid New Hires', value: paidNewFTE, sub: 'beyond current 13 FTE', color: 'rgb(71,11,0)' },
1077 { label: 'Engineering Cost/yr', value: '\u20AC' + (engCostPerYear / 1e6).toFixed(1) + 'M', sub: paidNewFTE + ' new FTE \u00D7 \u20AC' + (salary / 1000).toFixed(0) + 'k', color: 'rgb(71,11,0)' },
1078 { label: 'CX Investment/yr', value: '\u20AC' + (cxAnnual / 1000).toFixed(0) + 'k', sub: cxLabels[cxTier], color: '#8a5a00' },
1079 { label: 'Total ' + years + '-Year Cost', value: '\u20AC' + (totalCostSprint / 1e6).toFixed(1) + 'M', sub: 'eng + CX over ' + years + ' years', color: totalCostSprint > 15e6 ? '#a33' : 'rgb(71,11,0)' },
1080 ].map(c =>
1081 '<div style="background:rgba(71,11,0,0.05);border-radius:8px;padding:14px;text-align:center;border:1px solid rgba(71,11,0,0.15);">' +
1082 '<div style="font-size:11px;color:#666;text-transform:uppercase;letter-spacing:0.05em;margin-bottom:4px;">' + c.label + '</div>' +
1083 '<div style="font-size:24px;font-weight:700;color:' + c.color + ';">' + c.value + '</div>' +
1084 '<div style="font-size:11px;color:#686868;margin-top:2px;">' + c.sub + '</div>' +
1085 '</div>'
1086 ).join('');
1087
1088 // Year-by-year cost breakdown table
1089 const breakdownDiv = document.getElementById('sprintBreakdown');
1090 let tableRows = '';
1091 let cumulative = 0;
1092 for (let y = 1; y <= years; y++) {
1093 // Ramp: assume linear hiring over first year, so Y1 is 50% eng cost
1094 const rampFactor = y === 1 ? 0.5 : 1.0;
1095 const engY = engCostPerYear * rampFactor;
1096 const totalY = engY + cxCostPerYear;
1097 cumulative += totalY;
1098 tableRows += '<tr>' +
1099 '<td style="padding:6px 10px;border-bottom:1px solid rgba(71,11,0,0.08);">Year ' + y + '</td>' +
1100 '<td style="padding:6px 10px;text-align:right;border-bottom:1px solid rgba(71,11,0,0.08);">' + paidNewFTE + (y === 1 ? ' (ramping)' : '') + '</td>' +
1101 '<td style="padding:6px 10px;text-align:right;border-bottom:1px solid rgba(71,11,0,0.08);">\u20AC' + (engY / 1e6).toFixed(2) + 'M</td>' +
1102 '<td style="padding:6px 10px;text-align:right;border-bottom:1px solid rgba(71,11,0,0.08);">\u20AC' + (cxCostPerYear / 1e6).toFixed(2) + 'M</td>' +
1103 '<td style="padding:6px 10px;text-align:right;border-bottom:1px solid rgba(71,11,0,0.08);font-weight:700;">\u20AC' + (totalY / 1e6).toFixed(2) + 'M</td>' +
1104 '<td style="padding:6px 10px;text-align:right;border-bottom:1px solid rgba(71,11,0,0.08);color:#686868;">\u20AC' + (cumulative / 1e6).toFixed(2) + 'M</td>' +
1105 '</tr>';
1106 }
1107 breakdownDiv.innerHTML =
1108 '<table style="width:100%;border-collapse:collapse;font-size:13px;background:#fff;border-radius:8px;overflow:hidden;border:1px solid rgba(71,11,0,0.15);">' +
1109 '<tr style="background:rgba(71,11,0,0.05);"><th style="padding:6px 10px;text-align:left;color:rgb(71,11,0);">Period</th><th style="padding:6px 10px;text-align:right;color:#666;">New FTE</th><th style="padding:6px 10px;text-align:right;color:#666;">Engineering</th><th style="padding:6px 10px;text-align:right;color:#666;">CX</th><th style="padding:6px 10px;text-align:right;color:#666;">Total</th><th style="padding:6px 10px;text-align:right;color:#666;">Cumulative</th></tr>' +
1110 tableRows +
1111 '<tr style="background:rgba(71,11,0,0.08);font-weight:700;"><td style="padding:6px 10px;color:rgb(71,11,0);">Total</td><td style="padding:6px 10px;text-align:right;">' + paidNewFTE + '</td><td colspan="2" style="padding:6px 10px;"></td><td style="padding:6px 10px;text-align:right;color:rgb(71,11,0);">\u20AC' + (cumulative / 1e6).toFixed(2) + 'M</td><td style="padding:6px 10px;"></td></tr>' +
1112 '</table>' +
1113 '<p style="font-size:11px;color:#686868;margin-top:6px;">Year 1 engineering cost assumes 50% ramp (mid-year average for new hires). Community contribution offset: ' + communityFTE + ' FTE (' + (communityPct * 100).toFixed(0) + '%), saving \u20AC' + ((communityFTE * salary * years) / 1e6).toFixed(1) + 'M. Salary: \u20AC' + (salary / 1000).toFixed(0) + 'k avg. Engineering salary only \u2014 see Opex Addendum for full loaded costs.</p>';
1114
1115 // Sprint timeline chart: features passing over quarters
1116 const quarterLabels = [];
1117 const currentData = [];
1118 const sprintData = [];
1119 for (let q = 0; q <= targetQ; q++) {
1120 quarterLabels.push(q === 0 ? 'Now' : 'Q' + q);
1121 currentData.push(countPassing(sprintCurrentFTE));
1122 sprintData.push(countPassing(totalFTE));
1123 }
1124 // Recompute per-quarter for proper trajectory
1125 function countPassingAtQ(fte, maxQ) {
1126 const scale = Math.pow(fte / sprintCurrentFTE, exp);
1127 const feats = mtAllFeatures.filter(f => f.entryQ <= maxQ);
1128 let passing = 0;
1129 for (const f of feats) {
1130 if (f.score >= 0.95 && f.entryQ === 0) { passing++; continue; }
1131 let v = f.velocity;
1132 if (f.stalled) v = 0.02412099133410609;
1133 if (v <= 0.001) continue;
1134 const qAvail = Math.max(0, maxQ - f.entryQ);
1135 const projected = f.score + v * scale * qAvail;
1136 if (projected >= 0.95) passing++;
1137 }
1138 return passing;
1139 }
1140 const timelineQs = [];
1141 const timelineCurrent = [];
1142 const timelineSprint = [];
1143 const timelineBWA = [];
1144 for (let q = 0; q <= targetQ; q += 1) {
1145 timelineQs.push(q === 0 ? 'Now' : '+' + (q / 4).toFixed(q % 4 === 0 ? 0 : 1) + 'y');
1146 timelineCurrent.push(countPassingAtQ(sprintCurrentFTE, q));
1147 timelineSprint.push(countPassingAtQ(totalFTE, q));
1148 timelineBWA.push(mtAllFeatures.filter(f => f.entryQ <= q).length);
1149 }
1150
1151 if (window._sprintTimeline) window._sprintTimeline.destroy();
1152 window._sprintTimeline = new Chart(document.getElementById('sprintTimeline'), {
1153 type: 'line',
1154 data: {
1155 labels: timelineQs,
1156 datasets: [
1157 { label: 'BWA Total', data: timelineBWA, borderColor: '#a33', backgroundColor: 'rgba(204,68,68,0.05)', fill: true, tension: 0.3, pointRadius: 2, borderDash: [5, 3] },
1158 { label: 'At ' + totalFTE + ' FTE', data: timelineSprint, borderColor: '#1f6e1f', backgroundColor: 'rgba(42,125,42,0.1)', fill: true, tension: 0.3, pointRadius: 3 },
1159 { label: 'Current (13 FTE)', data: timelineCurrent, borderColor: 'rgb(71,11,0)', backgroundColor: 'transparent', tension: 0.3, pointRadius: 2, borderDash: [3, 3] },
1160 ]
1161 },
1162 options: {
1163 responsive: true, maintainAspectRatio: false,
1164 scales: { y: { min: 0, title: { display: true, text: 'Features' } } },
1165 plugins: {
1166 legend: { position: 'bottom', labels: { boxWidth: 12 } },
1167 title: { display: true, text: 'Feature Completion Trajectory (' + years + '-year sprint)', color: '#666' },
1168 }
1169 }
1170 });
1171
1172 // Cost breakdown chart
1173 const costLabels = [];
1174 const engCosts = [];
1175 const cxCostsArr = [];
1176 let cum = 0;
1177 for (let y = 1; y <= years; y++) {
1178 costLabels.push('Year ' + y);
1179 const ramp = y === 1 ? 0.5 : 1.0;
1180 engCosts.push(+(engCostPerYear * ramp / 1e6).toFixed(2));
1181 cxCostsArr.push(+(cxCostPerYear / 1e6).toFixed(2));
1182 }
1183
1184 if (window._sprintCost) window._sprintCost.destroy();
1185 window._sprintCost = new Chart(document.getElementById('sprintCostChart'), {
1186 type: 'bar',
1187 data: {
1188 labels: costLabels,
1189 datasets: [
1190 { label: 'Engineering', data: engCosts, backgroundColor: 'rgba(71,11,0,0.5)', borderColor: 'rgb(71,11,0)', borderWidth: 1 },
1191 { label: 'CX Investment', data: cxCostsArr, backgroundColor: 'rgba(138,90,0,0.5)', borderColor: '#8a5a00', borderWidth: 1 },
1192 ]
1193 },
1194 options: {
1195 responsive: true, maintainAspectRatio: false,
1196 scales: {
1197 x: { stacked: true },
1198 y: { stacked: true, title: { display: true, text: 'Cost (\u20ACM)' }, ticks: { callback: v => '\u20AC' + v + 'M' } },
1199 },
1200 plugins: {
1201 legend: { position: 'bottom', labels: { boxWidth: 12 } },
1202 title: { display: true, text: 'Annual Cost Breakdown', color: '#666' },
1203 }
1204 }
1205 });
1206 }
1207
1208 document.getElementById('sprintTarget').addEventListener('input', runSprint);
1209 document.getElementById('sprintYears').addEventListener('input', runSprint);
1210 document.getElementById('sprintSalary').addEventListener('input', runSprint);
1211 document.getElementById('sprintCommunity').addEventListener('input', runSprint);
1212 document.getElementById('sprintCX').addEventListener('change', runSprint);
1213 document.getElementById('sprintExp').addEventListener('input', runSprint);
1214 runSprint();
1215}
1216</script>
1217
1218</body>
1219</html>