  Network robustness plays a crucial role in our understanding of complex
interconnected systems such as transportation, communication, and computer
networks. While significant research has been conducted in the area of network
robustness, no comprehensive open-source toolbox currently exists to assist
researchers and practitioners in this important topic. This lack of available
tools hinders reproducibility and examination of existing work, development of
new research, and dissemination of new ideas. We contribute TIGER, an
open-sourced Python toolbox to address these challenges. TIGER contains 22
graph robustness measures with both original and fast approximate versions; 17
failure and attack strategies; 15 heuristic and optimization-based defense
techniques; and 4 simulation tools. By democratizing the tools required to
study network robustness, our goal is to assist researchers and practitioners
in analyzing their own networks; and facilitate the development of new research
in the field. TIGER has been integrated into the Nvidia Data Science Teaching
Kit available to educators across the world; and Georgia Tech's Data and Visual
Analytics class with over 1,000 students. TIGER is open sourced at:
https://github.com/safreita1/TIGER
