Developed and Optimized Graph Algorithms with DFS

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📅 2023-10-09 — Session: Developed and Optimized Graph Algorithms with DFS

🕒 05:00–05:55
🏷️ Labels: DFS, Graph Algorithms, Optimization, Memoization, Network Connectivity
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal: The session aimed to develop and optimize graph algorithms using Depth-First Search (DFS) techniques to determine network connectivity and identify critical connections or bridges.

Key Activities:

  • Implemented two DFS algorithms to assess network connectivity and identify isolated nodes due to attacks, focusing on time complexity of O(|C|).
  • Explored the identification of critical cables in a graph by recognizing bridges using DFS, enhancing efficiency by avoiding multiple DFS executions.
  • Discussed the algorithmic process for bridge identification in graphs, emphasizing discovery and low values for backtracking cycle detection.
  • Analyzed the complexity of the bridge identification algorithm, detailing the DFS operations and conditions for bridge detection.
  • Optimized the amigos_debajo function using memoization to reduce redundant calculations and improve performance.
  • Provided pseudocode for calculating nodes under a tree node in DFS, utilizing set operations for aggregation.

Achievements:

  • Successfully developed efficient graph algorithms with DFS for network analysis.
  • Improved algorithmic efficiency by adopting memoization techniques.

Pending Tasks:

  • Further testing and validation of the optimized algorithms in real-world scenarios.
  • Explore additional optimization techniques for large-scale graph data.

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