{'fraction_non_alphanumeric': 0.011750881316098707, 'fraction_numerical': 0.0, 'mean_word_length': 4.875862068965517, '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}}
Automatic detection of bad smells from excel sheets and refactor for performance improvement

This paper presents the prevailing analysis, as well as some of experimental findings analogous to the factual study of so called Bad smells. An anatomy is presented which categorize bad smells given by Fowler in context of object-oriented programming. Many research papers have been published quantifying the effect of code smells on maintenance efforts. Notion of bad smells can be applied to multiple areas other than Software. This paper intends to give a review to look for bad smells in the context of spreadsheets. Many authors in past years have worked on spreadsheet bad smells. Here in this paper, a systematic review is proposed demonstrating list of bad smells for spreadsheets and related work issued in past in field of spreadsheet bad smells.