{'fraction_non_alphanumeric': 0.017518248175182483, 'fraction_numerical': 0.004379562043795621, 'mean_word_length': 5.017543859649122, '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}}
Area-Time Efficient Self-Checking ALU Based on Scalable Error Detection Coding

In this paper, we propose a self-checking ALU based on Scalable Error Detection Coding (SEDC) algorithm which is capable of detecting 100% unidirectional errors. The SEDC encoded ALU is scalable based on the input data length. The area overhead increases only by a small factor with increase in data length while the computational latency remains constant irrespective of the binary data length. We show that the proposed scheme is faster and easily scalable compared with the previous implementations based on Berger and Bose-Lin codes and also more area efficient than Berger Check Prediction based ALU.