The third edition of this standard textbook of modern graph theory has been carefully revised, updated, and substantially extended.
Covering all its major recent developments it can be used both as a reliable textbook for an introductory course and as a graduate text: on each topic it covers all the basic
material in full detail, and adds one or two deeper results (again with detailed proofs)
to illustrate the more advanced methods of that field.

From the reviews of the first two editions (1997, 2000):

#  Background material
# Lecture 1: Introduction
# Lecture 2: Interval graphs
# Lecture 3: Chordal graphs
# Lecture 4: Recognizing chordal graphs
# Lecture 5: Comparability graphs
# Lecture 6: Recognizing interval graphs
# Lecture 7: Friends of interval graphs
# Lecture 8: Trees and treewidth
# Lecture 9: Partial k-trees. k-connectivity
# Lecture 10: 2-terminal SP-graphs
# Lecture 11: Dynamic programming on partial k-trees )
# Lecture 12: Separators in partial k-trees
# Lecture 13: End of partial k-trees

# Contents
# Chapter 1: Graphs and Subgraphs
# Chapter 2: Trees
# Chapter 3: Connectivity
# Chapter 4: Euler Tours and Hamilton Cycles
# Chapter 5: Matchings
# Chapter 6: Edge Colourings
# Chapter 7: Independent Sets and Cliques
# Chapter 8: Vertex Colourings
# Chapter 9: Planar Graphs
# Chapter 10: Directed Graphs
# Chapter 11: Networks
# Chapter 12: The Cycle Space and Bond Space
# Appendix 1: Hints to Starred Exercises
# Appendix II: Four Graphs and a Table of their Properties

# Lesson 1: Null graphs
# Lesson 2: Handshaking Lemma
# Lesson 3: Isomorphism
# Lesson 4: Complete Graphs, Subgraphs
# Lesson 5: Regular Graphs
# Lesson 6: Platonic Graphs
# Lesson 7: Adjacency Matrices
# Lesson 8: Graph Coloring
# Lesson 9: Bipartite Graphs
# Lesson 10: Stars and Tripartite Graphs
# Lesson 11: Circuits and Wheels
# Lesson 12: Euler Circuits, Hamilton Circuits and Directed Graphs
# Lesson 13: Trees and Searches
# Lesson 14: Unions and Sums
# Lesson 15: Complements
# Lesson 16: Prisms

The results of cache-simulation experiments with an abstract machine for reducing combinator graphs are presented. The abstract machine, called TIGRE, exhibits reduction rates that, for similar kinds of combinator graphs on similar kinds of hardware, compare favorably with previously reported techniques. Furthermore, TIGRE maps easily and efficiently onto standard computer architectures, particularly those that allow a restricted form of self-modifying code.