Advanced Algorithmic Techniques

This capstone unit explores advanced algorithmic methods and practical implementations that extend core algorithmic concepts into real-world problems such as graph analytics, compression, cryptography, and spatial computation. Students synthesize prior learning to implement, optimize, and reason about algorithm performance, correctness, security, and applicability in software and systems development contexts.

Learning Objectives

• Analyze graph-based data by representing relations, converting graphs to numeric formats, and applying shortest-path, PageRank-style, and link-analysis algorithms to extract and interpret network insights
• Apply algorithmic techniques to data transformation and optimization tasks including data compression, edit-distance reduction strategies, fast large-number multiplication, and fair-division/resource allocation methods
• Demonstrate implementation and evaluation of security and integrity mechanisms by designing one-way functions, unique identifier schemes, basic encryption approaches, and strategies for keeping data secret
• Evaluate algorithm behavior and limitations by reasoning about termination (halting), computational complexity, automation effects (automatic responses and bots), spatial considerations, and trade-offs between correctness, performance, and resource use