Weakness Analytics Engine
How CrackCode computes performance metrics and identifies blind spots.
Traditional platforms track your success metrics (problems solved, badges collected). CrackCode's Weakness Analytics engine is built to identify patterns of avoidance and algorithmic gaps.
Parsing the 8 Dimensions
Our analyzer parses submissions and tags them into 8 key modules:
1. Dynamic Programming
Interval DP, Digit DP, Bitmask DP, Knapsack, and state transition optimizations.
2. Graph Theory
Dijkstra, Bellman-Ford, Kruskal, DSU, LCA, Tarjan's strongly connected components.
3. Mathematics & Theory
Modular arithmetic, GCD, prime factorization, combinatorics, matrix exponentiation.
4. Greedy Algorithms
Huffman coding, fractional knapsack, interval scheduling, sorting-based greedy choices.
The Weakness Index Formula
For each sub-category, the engine computes a **Weakness Index (WI)** between 0 and 100:
// WI scales with difficulty weights and submission failures
WI = (W_attempts * 0.4) + (W_difficulty_gap * 0.4) + (W_avoidance_days * 0.2)
where W_attempts = Failed Submissions / Total Submissions
where W_difficulty_gap = (Target Difficulty - Mode Solved Difficulty)
Categories with a **WI > 60** are designated as **Critical Weaknesses**. The recommendation scheduler will prioritize these tags until the index falls below the active threshold.