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Module 3: Graph Algorithms & Network Analysis: Reading Guide

Do not read graph chapters front-to-back by default. Read to repair a specific gap.

Read Closely​

Read closely when the source explains a correctness idea or precondition:

  • BFS layer invariant
  • DFS timestamps and edge classification
  • Dijkstra's nonnegative-weight assumption
  • Bellman-Ford relaxation rounds
  • MST cut and cycle properties
  • residual graphs and augmenting paths
  • max-flow min-cut duality

After close reading, close the source and reconstruct the argument in your own words.

Skim​

Skim for vocabulary and extra variants:

  • graph taxonomy lists
  • advanced flow algorithms beyond Edmonds-Karp
  • specialized graph families not used in this module
  • implementation language details that do not match your chosen language

Capture terms, but do not turn every side path into a requirement.

Skip For Now​

Skip until later unless your project demands it:

  • planarity algorithms
  • graph minors
  • advanced matching theory
  • distributed graph processing systems
  • approximation algorithms for NP-hard graph problems

These are real topics, but they are not required to complete this module.

Stop-Reading Rules​

Stop reading and solve when you can:

  • model the graph before naming the algorithm
  • explain why the algorithm's preconditions fit
  • trace the algorithm on 5-8 vertices
  • name the running time
  • produce one counterexample for a wrong algorithm choice

Exercise Reading Rule​

For book exercises, read only enough surrounding text to solve the next problem. If you need more than 20 minutes of reading before attempting a problem, switch to a smaller example or a worked trace first.