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UML for Java Programmers

* *Compliant and up-to-date with the latest version of the industry standard for modelling software programs, UML 2.0 *Concise and practical; written for the Java programmer *Contains thorough Java code examples AND their related UML diagrams -- a critical and proven approach to learning

If that language is Java, you need "UML for Java Programmers." In this book, one of the world's leading object design experts becomes your personal coach on UML 1&2 techniques and best practices for the Java environment.

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ALGORITHM DESIGN: FOUNDATION, ANALYSIS AND INTERNET EXAMPLES

Market_Desc: · Computer Programmers· Software Engineers· Scientists Special Features: · Addresses the issue of the implementation of data structures and algorithms· Covers Cryptology, FFTs, Parallel algorithms, and NP-completeness About The Book: This text addresses the often neglected issue of how to actually implement data structures and algorithms. The title Algorithm Engineering reflects the authors' approach that designing and implementing algorithms takes more than just the theory of algorithms. It also involves engineering design principles, such as abstract data types, object-orient design patterns, and software use and robustness issues.

Market_Desc: · Computer Programmers· Software Engineers· Scientists Special Features: · Addresses the issue of the implementation of data structures and algorithms· Covers Cryptology, FFTs, Parallel algorithms, and NP-completeness ...

Parallel Algorithm Derivation and Program Transformation

Transformational programming and parallel computation are two emerging fields that may ultimately depend on each other for success. Perhaps because ad hoc programming on sequential machines is so straightforward, sequential programming methodology has had little impact outside the academic community, and transformational methodology has had little impact at all. However, because ad hoc programming for parallel machines is so hard, and because progress in software construction has lagged behind architectural advances for such machines, there is a much greater need to develop parallel programming and transformational methodologies. Parallel Algorithm Derivation and Program Transformation stimulates the investigation of formal ways to overcome problems of parallel computation, with respect to both software development and algorithm design. It represents perspectives from two different communities: transformational programming and parallel algorithm design, to discuss programming, transformational, and compiler methodologies for parallel architectures, and algorithmic paradigms, techniques, and tools for parallel machine models. Parallel Algorithm Derivation and Program Transformation is an excellent reference for graduate students and researchers in parallel programming and transformational methodology. Each chapter contains a few initial sections in the style of a first-year, graduate textbook with many illustrative examples. The book may also be used as the text for a graduate seminar course or as a reference book for courses in software engineering, parallel programming or formal methods in program development.

This book contains selected papers from the ONR Workshop on Parallel Algorithm Design and Program Transformation that took place at New York University, Courant Institute, from Aug. 30 to Sept. 1, 1991.

Proceedings of the Eighth Workshop on Algorithm Engineering and Experiments and the Third Workshop on Analytic Algorithmics and Combinatorics

The annual Workshop on Algorithm Engineering and Experiments (ALENEX) provides a forum for the presentation of original research in all aspects of algorithm engineering, including the implementation and experimental evaluation of algorithms and data structures. The workshop was sponsored by SIAM, the Society for Industrial and Applied Mathematics, and SIGACT, the ACM Special Interest Group on Algorithms and Computation Theory. The aim of ANALCO is to provide a forum for the presentation of original research in the analysis of algorithms and associated combinatorial structures.