Refactor analytics aggregation with structure-preserving optimization

[ash1shkumar]

📌 Description

This PR refactors the analytics aggregation system to improve consistency, maintainability, and performance of multi-stage data computations.

The previous implementation performed repeated per-user scans and unindexed message filtering, leading to unnecessary computational overhead in large datasets.

This update preserves the existing API structure while optimizing internal aggregation logic.

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⚙️ Changes Made

🔹 Performance Optimization

• Introduced pre-indexed messagesByUser map to avoid repeated filtering
• Reduced nested iteration complexity in user activity calculation
• Optimized sprint splitting logic for deterministic execution

🔹 Structural Preservation

• Maintained all existing helper functions and API response shape
• No breaking changes to frontend consumers
• Preserved metadata and execution context objects

🔹 Data Consistency Improvements

• Ensured deterministic sorting of events
• Stabilized sprint assignment logic
• Improved aggregation traceability

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📂 Affected Areas

• Analytics aggregation controller
• Request-level computation pipeline
• User activity calculation logic

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🎯 Impact

Performance

• Reduced redundant iterations over messages/tasks
• Improved scalability for large datasets

Reliability

• More consistent aggregation outputs
• Eliminated inconsistent per-request drift

Maintainability

• Cleaner separation of aggregation steps
• Easier debugging and extension of analytics logic

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🧪 Testing Checklist

• Analytics API returns valid response shape
• Sprint separation works correctly
• User activity counts remain accurate
• No breaking changes to frontend consumers
• Handles empty datasets safely

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Fixes #362

🏷 Expected Labels

level3, NSoC'26

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