feat: enhance Jira dashboard with export functionality and sprint comparison
- Added export options for CSV and JSON in `JiraDashboardPageClient`, allowing users to download metrics easily. - Integrated `SprintComparison` component to visualize inter-sprint trends and predictions. - Updated TODO.md to reflect completion of export metrics and sprint comparison features.
This commit is contained in:
336
components/jira/SprintComparison.tsx
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336
components/jira/SprintComparison.tsx
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'use client';
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import { LineChart, Line, XAxis, YAxis, CartesianGrid, Tooltip, ResponsiveContainer, BarChart, Bar, Cell } from 'recharts';
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import { SprintVelocity } from '@/lib/types';
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import { Card, CardContent, CardHeader } from '@/components/ui/Card';
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interface SprintComparisonProps {
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sprintHistory: SprintVelocity[];
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className?: string;
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}
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interface ComparisonMetrics {
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velocityTrend: 'improving' | 'declining' | 'stable';
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avgCompletion: number;
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consistency: 'high' | 'medium' | 'low';
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bestSprint: SprintVelocity;
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worstSprint: SprintVelocity;
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predictions: {
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nextSprintEstimate: number;
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confidenceLevel: 'high' | 'medium' | 'low';
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};
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}
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export function SprintComparison({ sprintHistory, className }: SprintComparisonProps) {
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// Analyser les tendances
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const metrics = analyzeSprintTrends(sprintHistory);
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// Données pour les graphiques
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const comparisonData = sprintHistory.map(sprint => ({
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name: sprint.sprintName.replace('Sprint ', ''),
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completion: sprint.completionRate,
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velocity: sprint.completedPoints,
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planned: sprint.plannedPoints,
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variance: sprint.plannedPoints > 0
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? ((sprint.completedPoints - sprint.plannedPoints) / sprint.plannedPoints) * 100
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: 0
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}));
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const CustomTooltip = ({ active, payload, label }: {
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active?: boolean;
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payload?: Array<{ value: number; name: string; color: string }>;
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label?: string
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}) => {
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if (active && payload && payload.length) {
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return (
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<div className="bg-[var(--card)] border border-[var(--border)] rounded-lg p-3 shadow-lg">
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<p className="font-medium text-sm mb-2">Sprint {label}</p>
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<div className="space-y-1 text-xs">
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{payload.map((item, index) => (
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<div key={index} className="flex justify-between gap-4">
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<span style={{ color: item.color }}>{item.name}:</span>
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<span className="font-mono" style={{ color: item.color }}>
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{typeof item.value === 'number' ?
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(item.name.includes('%') ? `${item.value}%` : item.value) :
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item.value
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}
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</span>
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</div>
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))}
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</div>
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</div>
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);
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}
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return null;
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};
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return (
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<div className={className}>
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<div className="grid grid-cols-1 lg:grid-cols-2 gap-6">
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{/* Graphique de comparaison des taux de complétion */}
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<div>
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<h4 className="text-sm font-medium mb-3">Évolution des taux de complétion</h4>
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<div style={{ width: '100%', height: '200px' }}>
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<ResponsiveContainer width="100%" height="100%">
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<LineChart data={comparisonData} margin={{ top: 20, right: 30, left: 20, bottom: 20 }}>
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<CartesianGrid strokeDasharray="3 3" stroke="var(--border)" />
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<XAxis
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dataKey="name"
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stroke="var(--muted-foreground)"
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fontSize={10}
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/>
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<YAxis
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stroke="var(--muted-foreground)"
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fontSize={10}
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domain={[0, 100]}
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label={{ value: '%', angle: 0, position: 'insideLeft' }}
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/>
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<Tooltip content={<CustomTooltip />} />
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<Line
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type="monotone"
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dataKey="completion"
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stroke="hsl(217, 91%, 60%)"
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strokeWidth={3}
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dot={{ fill: 'hsl(217, 91%, 60%)', strokeWidth: 2, r: 5 }}
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name="Taux de complétion"
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/>
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</LineChart>
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</ResponsiveContainer>
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</div>
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</div>
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{/* Graphique de comparaison des vélocités */}
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<div>
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<h4 className="text-sm font-medium mb-3">Comparaison planifié vs réalisé</h4>
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<div style={{ width: '100%', height: '200px' }}>
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<ResponsiveContainer width="100%" height="100%">
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<BarChart data={comparisonData} margin={{ top: 20, right: 30, left: 20, bottom: 20 }}>
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<CartesianGrid strokeDasharray="3 3" stroke="var(--border)" />
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<XAxis
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dataKey="name"
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stroke="var(--muted-foreground)"
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fontSize={10}
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/>
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<YAxis
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stroke="var(--muted-foreground)"
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fontSize={10}
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/>
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<Tooltip content={<CustomTooltip />} />
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<Bar dataKey="planned" name="Planifié" fill="hsl(240, 5%, 64%)" radius={[2, 2, 0, 0]} />
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<Bar dataKey="velocity" name="Réalisé" fill="hsl(217, 91%, 60%)" radius={[2, 2, 0, 0]} />
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</BarChart>
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</ResponsiveContainer>
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</div>
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</div>
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</div>
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{/* Métriques de comparaison */}
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<div className="mt-6 grid grid-cols-2 lg:grid-cols-4 gap-4">
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<Card className="p-3">
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<div className="text-center">
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<div className={`text-lg font-bold ${
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metrics.velocityTrend === 'improving' ? 'text-green-500' :
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metrics.velocityTrend === 'declining' ? 'text-red-500' : 'text-blue-500'
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}`}>
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{metrics.velocityTrend === 'improving' ? '📈' :
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metrics.velocityTrend === 'declining' ? '📉' : '➡️'}
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</div>
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<div className="text-xs text-[var(--muted-foreground)] mt-1">
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Tendance générale
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</div>
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</div>
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</Card>
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<Card className="p-3">
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<div className="text-center">
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<div className={`text-lg font-bold ${
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metrics.avgCompletion > 80 ? 'text-green-500' :
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metrics.avgCompletion > 60 ? 'text-orange-500' : 'text-red-500'
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}`}>
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{Math.round(metrics.avgCompletion)}%
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</div>
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<div className="text-xs text-[var(--muted-foreground)] mt-1">
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Complétion moyenne
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</div>
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</div>
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</Card>
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<Card className="p-3">
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<div className="text-center">
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<div className={`text-lg font-bold ${
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metrics.consistency === 'high' ? 'text-green-500' :
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metrics.consistency === 'medium' ? 'text-orange-500' : 'text-red-500'
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}`}>
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{metrics.consistency === 'high' ? 'Haute' :
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metrics.consistency === 'medium' ? 'Moyenne' : 'Faible'}
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</div>
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<div className="text-xs text-[var(--muted-foreground)] mt-1">
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Consistance
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</div>
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</div>
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</Card>
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<Card className="p-3">
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<div className="text-center">
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<div className={`text-lg font-bold ${
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metrics.predictions.confidenceLevel === 'high' ? 'text-green-500' :
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metrics.predictions.confidenceLevel === 'medium' ? 'text-orange-500' : 'text-red-500'
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}`}>
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{metrics.predictions.nextSprintEstimate}
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</div>
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<div className="text-xs text-[var(--muted-foreground)] mt-1">
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Prédiction suivante
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</div>
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</div>
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</Card>
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</div>
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{/* Insights et recommandations */}
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<div className="mt-6 grid grid-cols-1 lg:grid-cols-2 gap-4">
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<Card className="p-4">
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<h4 className="text-sm font-medium mb-3">🏆 Meilleur sprint</h4>
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<div className="space-y-2 text-sm">
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<div className="flex justify-between">
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<span>Sprint:</span>
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<span className="font-semibold">{metrics.bestSprint.sprintName}</span>
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</div>
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<div className="flex justify-between">
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<span>Points complétés:</span>
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<span className="font-semibold text-green-500">{metrics.bestSprint.completedPoints}</span>
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</div>
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<div className="flex justify-between">
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<span>Taux de complétion:</span>
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<span className="font-semibold text-green-500">{metrics.bestSprint.completionRate}%</span>
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</div>
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</div>
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</Card>
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<Card className="p-4">
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<h4 className="text-sm font-medium mb-3">📉 Sprint à améliorer</h4>
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<div className="space-y-2 text-sm">
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<div className="flex justify-between">
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<span>Sprint:</span>
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<span className="font-semibold">{metrics.worstSprint.sprintName}</span>
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</div>
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<div className="flex justify-between">
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<span>Points complétés:</span>
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<span className="font-semibold text-red-500">{metrics.worstSprint.completedPoints}</span>
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</div>
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<div className="flex justify-between">
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<span>Taux de complétion:</span>
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<span className="font-semibold text-red-500">{metrics.worstSprint.completionRate}%</span>
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</div>
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</div>
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</Card>
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</div>
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{/* Recommandations */}
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<Card className="mt-4 p-4">
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<h4 className="text-sm font-medium mb-2">💡 Recommandations</h4>
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<div className="space-y-2 text-sm">
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{getRecommendations(metrics).map((recommendation, index) => (
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<div key={index} className="flex items-start gap-2">
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<span className="text-blue-500 mt-0.5">•</span>
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<span>{recommendation}</span>
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</div>
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))}
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</div>
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</Card>
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</div>
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);
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}
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/**
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* Analyse les tendances des sprints
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*/
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function analyzeSprintTrends(sprintHistory: SprintVelocity[]): ComparisonMetrics {
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if (sprintHistory.length === 0) {
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return {
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velocityTrend: 'stable',
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avgCompletion: 0,
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consistency: 'low',
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bestSprint: sprintHistory[0],
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worstSprint: sprintHistory[0],
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predictions: { nextSprintEstimate: 0, confidenceLevel: 'low' }
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};
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}
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// Tendance de vélocité (comparer premiers vs derniers sprints)
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const firstHalf = sprintHistory.slice(0, Math.ceil(sprintHistory.length / 2));
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const secondHalf = sprintHistory.slice(Math.floor(sprintHistory.length / 2));
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const firstHalfAvg = firstHalf.reduce((sum, s) => sum + s.completedPoints, 0) / firstHalf.length;
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const secondHalfAvg = secondHalf.reduce((sum, s) => sum + s.completedPoints, 0) / secondHalf.length;
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const improvementRate = (secondHalfAvg - firstHalfAvg) / firstHalfAvg * 100;
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const velocityTrend: 'improving' | 'declining' | 'stable' =
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improvementRate > 10 ? 'improving' :
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improvementRate < -10 ? 'declining' : 'stable';
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// Complétion moyenne
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const avgCompletion = sprintHistory.reduce((sum, s) => sum + s.completionRate, 0) / sprintHistory.length;
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// Consistance (variance des taux de complétion)
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const completionRates = sprintHistory.map(s => s.completionRate);
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const variance = completionRates.reduce((sum, rate) => sum + Math.pow(rate - avgCompletion, 2), 0) / completionRates.length;
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const standardDeviation = Math.sqrt(variance);
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const consistency: 'high' | 'medium' | 'low' =
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standardDeviation < 10 ? 'high' :
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standardDeviation < 20 ? 'medium' : 'low';
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// Meilleur et pire sprint
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const bestSprint = sprintHistory.reduce((best, current) =>
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current.completionRate > best.completionRate ? current : best);
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const worstSprint = sprintHistory.reduce((worst, current) =>
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current.completionRate < worst.completionRate ? current : worst);
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// Prédiction pour le prochain sprint
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const recentSprints = sprintHistory.slice(-3); // 3 derniers sprints
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const recentAvg = recentSprints.reduce((sum, s) => sum + s.completedPoints, 0) / recentSprints.length;
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const nextSprintEstimate = Math.round(recentAvg);
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const confidenceLevel: 'high' | 'medium' | 'low' =
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consistency === 'high' && velocityTrend !== 'declining' ? 'high' :
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consistency === 'medium' ? 'medium' : 'low';
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return {
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velocityTrend,
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avgCompletion,
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consistency,
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bestSprint,
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worstSprint,
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predictions: { nextSprintEstimate, confidenceLevel }
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};
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}
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/**
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* Génère des recommandations basées sur l'analyse
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*/
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function getRecommendations(metrics: ComparisonMetrics): string[] {
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const recommendations: string[] = [];
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if (metrics.velocityTrend === 'declining') {
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recommendations.push("Tendance en baisse détectée - Identifier les blockers récurrents");
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recommendations.push("Revoir les estimations ou la complexité des tâches récentes");
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} else if (metrics.velocityTrend === 'improving') {
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recommendations.push("Excellente progression ! Maintenir les bonnes pratiques actuelles");
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}
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if (metrics.avgCompletion < 60) {
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recommendations.push("Taux de complétion faible - Considérer des sprints plus courts ou moins ambitieux");
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} else if (metrics.avgCompletion > 90) {
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recommendations.push("Taux de complétion très élevé - L'équipe pourrait prendre plus d'engagements");
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}
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if (metrics.consistency === 'low') {
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recommendations.push("Consistance faible - Améliorer la prévisibilité des estimations");
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recommendations.push("Organiser des rétrospectives pour identifier les causes de variabilité");
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}
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if (recommendations.length === 0) {
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recommendations.push("Performance stable et prévisible - Continuer sur cette lancée !");
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}
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return recommendations;
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}
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