{'fraction_non_alphanumeric': 0.0176017601760176, 'fraction_numerical': 0.0, 'mean_word_length': 5.5, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
FIRST-ORDER TERM COMPRESSION: TECHNIQUES AND APPLICATIONS

Lossless sequential data compression techniques are well-known. Such techniques work best on data with repetition in its sequential representation. One might wish to compress data that can possess non-sequential repetitive structure, for example, first-order terms. Sequential techniques often do not compress such data well. This paper presents improved compression techniques that can take advantage of repetitive term structure. The first part presents a formal background for the problem of compressing terms. The second part outlines several approaches to compressing terms by pattern substitution, using a modified form of substitution tree indexing. The third part shows how term compression can be used to compress proofs in a system for mobile code safety and presents experimental results establishing the effectiveness of term compression.