{'fraction_non_alphanumeric': 0.014778325123152709, 'fraction_numerical': 0.0, 'mean_word_length': 5.630434782608695, '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}}
Towards Probabilistic Assessment of Modularity

With recent trends showing increasing rates of software evolution and complexity, modularity is more important than it ever has been for on-time, on-budget software development. Assessing modularity is important for both evaluating current software quality and planning future changes. This latter use case is becoming more relevant as open-source models become more common and developers contribute to code with which they may be quite unfamiliar. Software engineers tasked with implementing specific changes to unfamiliar software might ask questions such as: