Data Structure Techniques

Data Structure Techniques

Data Structures in Pascal

This is a revision of the authors 1982 volume into Pascal, the language most widely used for teaching data structures. Data structures are central to computer science, and in particular to programming. In the analytic areas, appropriate data structures have been the key to advances in the design of algorithms. Once appropriate data structures are carefully defined, all that remains is routine coding. A comprehensive understanding of data structure techniques is essential in the design of algorithms and programs. This text presents a carefully chosen fraction of available material, but supplement it with a wide variety of exercises. No single book can discuss all known data structures or algorithms. This text presents the art of designing data structures, preparing the student to devise special-purpose structures for specific problems as they present themselves.

Advanced Theories and Computational Approaches to the Electronic Structure of Molecules

That there have been remarkable advances in the field of molecular electronic structure during the last decade is clear not only to those working in the field but also to anyone else who has used quantum chemical results to guide their own investiga tions. The progress in calculating the electronic structures of molecules has occurred through the truly ingenious theoretical and methodological developments that have made computationally tractable the underlying physics of electron distributions around a collection of nuclei. At the same time there has been consider able benefit from the great advances in computer technology. The growing sophistication, declining costs and increasing accessibi lity of computers have let theorists apply their methods to prob lems in virtually all areas of molecular science. Consequently, each year witnesses calculations on larger molecules than in the year before and calculations with greater accuracy and more com plete information on molecular properties. We can surely anticipate continued methodological develop ments of real consequence, and we can also see that the advance in computational capability is not about to slow down. The recent introduction of array processors, mUltiple processors and vector machines has yielded a tremendous acceleration of many types of computation, including operations typically performed in quantum chemical studies. Utilizing such new computing power to the ut most has required some new ideas and some reformulations of existing methods.