Large Problems, Small Machines: Transforming Your Programs with Advanced Algorithms describes a practical, real-world approach to program optimization based on advanced algorithms. Topics covered range from how to save storage using a restricted character set and how to speed up access to records by employing hash coding (or "e;scatter storage"e;) and caching. A selective mailing list system is used to illustrate rapid access to and rearrangement of information selected by criteria specified at run-time. Comprised of six chapters, this book begins by discussing factors to consider when deciding whether a program needs optimization. In the next chapter, a supermarket price lookup system is used to illustrate how to save storage by using a restricted character set and how to speed up access to records with the aid of hash coding and caching. Attention is paid to rapid retrieval of prices. A selective mailing list system is then used to illustrate rapid access to and rearrangement of information selected by criteria specified at run-time. The book also considers the Huffman coding and arithmetic coding methods of data compression before concluding with a review of the characteristics of the algorithms encountered in previous chapters, as well as the future of the art of optimization. This monograph will be a useful resource for practicing computer programmers and those who intend to be working programmers.

Large Problems, Small Machines: Transforming Your Programs with Advanced Algorithms describes a practical, real-world approach to program optimization based on advanced algorithms. Topics covered range from how to save storage using a restricted character set and how to speed up access to records by employing hash coding (or "e;scatter storage"e;) and caching. A selective mailing list system is used to illustrate rapid access to and rearrangement of information selected by criteria specified at run-time. Comprised of six chapters, this book begins by discussing factors to consider when deciding whether a program needs optimization. In the next chapter, a supermarket price lookup system is used to illustrate how to save storage by using a restricted character set and how to speed up access to records with the aid of hash coding and caching. Attention is paid to rapid retrieval of prices. A selective mailing list system is then used to illustrate rapid access to and rearrangement of information selected by criteria specified at run-time. The book also considers the Huffman coding and arithmetic coding methods of data compression before concluding with a review of the characteristics of the algorithms encountered in previous chapters, as well as the future of the art of optimization. This monograph will be a useful resource for practicing computer programmers and those who intend to be working programmers.