A Comparative Study of Text-Based Lossless Compression

Lossless data compression is a critical technique used to reduce file sizes without any loss of information during the encoding and decoding processes. This study presents a comparative analysis of two widely-used lossless compression algorithms: Huffman Encoding and Lempel-Ziv-Welch (LZW). The primary objective is to evaluate the performance of these algorithms in terms of compression ratio, compression time, decompression time, and space savings. The analysis was conducted on 100 files of varying sizes. The results demonstrate that the LZW algorithm outperforms Huffman Encoding, offering superior compression ratios, faster compression and decompression times, and greater disk space savings. These findings highlight the effectiveness of LZW for efficient data compression in practical applications.