{'fraction_non_alphanumeric': 0.016149068322981366, 'fraction_numerical': 0.0, 'mean_word_length': 4.676056338028169, '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}}
A novel approach to effective detection and analysis of code clones

Code clones are found in most of the software systems. They play a major role in the field of software engineering. The presence of clones in a particular module will either improve or degrade the quality of the overall software system. Poor quality software indirectly leads to strenuous software maintenance. Detecting the code clones will also pave way for analyzing them. The existing approaches detect the clones efficiently. Though some of the tools analyze the clones, accuracy is still missing. In this paper, a novel method is proposed, which exhibits the use of an efficient data mining technique in the phase of analysis. Based on the outcome of the analysis, the clones are either removed or retained in the software system.