Until now, no other book examined the gap between the theory of algorithms and the production of software programs. Focusing on practical issues, A Programmer's Companion to Algorithm Analysis carefully details the transition from the design and analysis of an algorithm to the resulting software program.
Consisting of two main complementary parts, the book emphasizes the concrete aspects of translating an algorithm into software that should perform based on what the algorithm analysis indicated. In the first part, the author describes the idealized universe that algorithm designers inhabit while the second part outlines how this ideal can be adapted to the real world of programming. The book explores analysis techniques, including crossover points, the influence of the memory hierarchy, implications of programming language aspects, such as recursion, and problems arising from excessively high computational complexities of solution methods. It concludes with four appendices that discuss basic algorithms; memory hierarchy, virtual memory management, optimizing compilers, and garbage collection; NP-completeness and higher complexity classes; and undecidability in practical terms.
Applying the theory of algorithms to the production of software, A Programmer's Companion to Algorithm Analysis fulfills the needs of software programmers and developers as well as students by showing that with the correct algorithm, you can achieve a functional software program.
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Ernst L. Leiss
Focusing on practical issues, A Programmer's Companion to Algorithm Analysis bridges the gap between algorithms and software programs. This book explains the fundamental differences between the computational model assumed for algorithms and the real architectures in which programs execute. It highlights the pitfalls that can occur when implementing an algorithm as software and offers suggestions to solve these problems. The book also explores the interactions among program, compiler, and run-time support system, contrasting this with the simpler model assumed for algorithms. Intended for software developers and programmers, it places particular emphasis on the implications of the memory hierarchy on program efficiency.
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