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Problem solving is an essential part of every scientific discipline. It has two components: (1) problem identification and formulation, and (2) the solution to the formulated problem. One can solve a problem on its own using ad hoc techniques or by following techniques that have produced efficient solutions to similar problems. This requires the understanding of various algorithm design techniques, how and when to use them to formulate solutions, and the context appropriate for each of them.Algorithms: Design Techniques and Analysis advocates the study of algorithm design by presenting the most useful techniques and illustrating them with numerous examples - emphasizing on design techniques in problem solving rather than algorithms topics like searching and sorting. Algorithmic analysis in connection with example algorithms are explored in detail. Each technique or strategy is covered in its own chapter through numerous examples of problems and their algorithms.Readers will be equipped with problem solving tools needed in advanced courses or research in science and engineering.

An introduction to the field of CAD for VLSI. It covers all aspects of physical design, together with such related fields as automatic cell generation, silicon compilation, layout editors and compaction. A problem-solving approach is adopted and each solution is illustrated with examples.

The book presents the important fundamental theorems and algorithms on planar graph drawing with easy-to-understand and constructive proofs. Extensively illustrated and with exercises included at the end of each chapter, it is suitable for use in advanced undergraduate and graduate level courses on algorithms, graph theory, graph drawing, information visualization and computational geometry. The book will also serve as a useful reference source for researchers in the field of graph drawing and software developers in information visualization, VLSI design and CAD.

Aims to highlight computational techniques related to algebraic curves. This book covers topics in this area, including elliptic curve cryptography, hyper elliptic curves, representations on some Riemann-Roch spaces of modular curves, computation of Hurwitz spectra, generating systems of finite groups, and Galois groups of polynomials.

Problem solving is an essential part of every scientific discipline. It has two components: (1) problem identification and formulation, and (2) the solution to the formulated problem. One can solve a problem on its own using ad hoc techniques or by following techniques that have produced efficient solutions to similar problems. This required the understanding of various algorithm design techniques, how and when to use them to formulate solutions, and the context appropriate for each of them.This book presents a design thinking approach to problem solving in computing - by first using algorithmic analysis to study the specifications of the problem, before mapping the problem on to data structures, then on to the situatable algorithms. Each technique or strategy is covered in its own chapter supported by numerous examples of problems and their algorithms. The new edition includes a comprehensive chapter on parallel algorithms, and many enhancements.