Arithmetic coding is a data compression technique that outperforms the widely used Huffman coding method. It provides better compression, is faster for adaptive models, and separates the model from the channel encoding. The paper presents an accessible implementation of arithmetic coding and discusses its performance characteristics. It reviews basic data compression concepts and introduces the model-based approach used in modern techniques. The paper outlines arithmetic coding using a simple example and provides programs for both encoding and decoding. The model is implemented as a separate module, allowing different models to be used easily. The paper discusses the construction of fixed and adaptive models, and details the compression efficiency and execution time of the programs, including the effect of different arithmetic word lengths on compression efficiency. It also outlines applications where arithmetic coding is appropriate. The paper explains that arithmetic coding represents information more compactly than Huffman coding, especially when the model probabilities are not integral powers of 1/2. It achieves the theoretical entropy bound for compression efficiency. The paper also discusses the implementation of arithmetic coding in C, including the encoding and decoding algorithms, and the use of fixed and adaptive models. It presents performance results for encoding and decoding 100,000-byte files on different platforms, showing that arithmetic coding is efficient and effective. The paper concludes that arithmetic coding is a superior method for data compression compared to Huffman coding.Arithmetic coding is a data compression technique that outperforms the widely used Huffman coding method. It provides better compression, is faster for adaptive models, and separates the model from the channel encoding. The paper presents an accessible implementation of arithmetic coding and discusses its performance characteristics. It reviews basic data compression concepts and introduces the model-based approach used in modern techniques. The paper outlines arithmetic coding using a simple example and provides programs for both encoding and decoding. The model is implemented as a separate module, allowing different models to be used easily. The paper discusses the construction of fixed and adaptive models, and details the compression efficiency and execution time of the programs, including the effect of different arithmetic word lengths on compression efficiency. It also outlines applications where arithmetic coding is appropriate. The paper explains that arithmetic coding represents information more compactly than Huffman coding, especially when the model probabilities are not integral powers of 1/2. It achieves the theoretical entropy bound for compression efficiency. The paper also discusses the implementation of arithmetic coding in C, including the encoding and decoding algorithms, and the use of fixed and adaptive models. It presents performance results for encoding and decoding 100,000-byte files on different platforms, showing that arithmetic coding is efficient and effective. The paper concludes that arithmetic coding is a superior method for data compression compared to Huffman coding.