Terrier is a modular platform for the rapid development of large-scale Information Retrieval applications, providing indexing and retrieval functionalities. Terrier is based on the Divergence from Randomness (DFR) framework. It can index various document collections, including the standard TREC collections, such as AP, WSJ, WT10G, .GOV and .GOV2. It also provides a wide range of parameter-free weighting approaches and full-text search algorithms, aiming to offer a public testbed for performing Information Retrieval experiments.