### Algorithms and Data Structures: With Applications to Graphics and Geometry

by **Jurg Nievergelt, Klaus Hinrichs – Prentice Hall, 2011**. Contents: Programming environments for motion, graphics, and geometry; Programming concepts – beyond notation; Objects, algorithms, programs; Complexity of problems and algorithms; Data structures; Interaction between algorithms and data structures.

### Data Structures and Algorithms

by **K. Mehlhorn and P. Sanders**

### LEDA: A Platform for Combinatorial and Geometric Computing

by **K. Mehlhorn, St. NÃ¤her**

The book treats the architecture, the implementation, and the use of the LEDA system. LEDA is a library of efficient data types and algorithms and a platform for combinatorial and geometric computing, written in C++ and freely available worldwide.

### Fundamental Data Structures

**Wikipedia, 2011**

A data structure is a particular way of storing and organizing data in a computer so that it can be used efficiently. Contents of the book: Sequences; Dictionaries; Sets; Priority queues; Successors and neighbors; Integer and string searching.

### Code Complete

by **Steve McConnell**

Widely considered one of the best practical guides to programming, Steve McConnellâ€™s original CODE COMPLETE has been helping developers write better software for more than a decade. Now this classic book has been fully updated and revised with leading-edge practicesâ€”and hundreds of new code samplesâ€”illustrating the art and science of software construction.

### Data Structures and Algorithms with Object-Oriented Design Patterns in java

by **Bruno R. Preiss B.A.Sc., M.A.Sc., Ph.D., P.Eng.**

### Art Gallery Theorems and Algorithms

by **Joseph O’Rourke**

This book is the most comprehensive collection of results on polygons currently available and thus earns its place as a standard text in computational geometry.

### Problems on Algorithms

by **Ian Parberry, William Gasarch**

### Data Structures and Algorithm Analysis in C++

by **Clifford A. Shaffer**

### Algorithmic Game Theory

by Noam Nisan, Tim Roughgarden, Eva Tardos, Vijay V. Vazirani

### Think Complexity

by Allen B. Downey

This book is about complexity science, data structures and algorithms, intermediate programming in Python, and the philosophy of science:

### Clever Algorithms: Nature-Inspired Programming Recipes

The book describes 45 algorithms from the field of Artificial Intelligence. All algorithm descriptions are complete and consistent to ensure that they are accessible, usable and understandable by a wide audience

### The Algorithm Design Manual

by Steven S. Skiena

This book serves as the primary textbook for any algorithm design course while maintaining its status as the premier practical reference guide to algorithms, intended as a manual on algorithm design for both students and computer professionals.

### Introduction to Design Analysis of Algorithms

by K. Raghava Rao

This book was very useful to easily understand the algorithms. This book is having enough examples on every algorithm. It has written for the sake of students to provide complete knowledge on Algorithms.

### Matters Computational: Ideas, Algorithms, Source Code

by Joerg Arndt, 2010

This is a book for a working programmer or anyone interested in methods of computation. The focus is on material that does not usually appear in textbooks on algorithms. We use the C++ programming language for low-level algorithms.

### Algorithm Implementation

Wikibooks, 2010

This book shows how common algorithms are written in various programming languages, providing code implementations and explanation. Topics: Checksums; Date and time; Graphs; Hashing; Optimization; Search; Simulation; Sorting; String searching; etc.

### Sequential and Parallel Sorting Algorithms

by H. W. Lang – FH Flensburg, 2000

From the table of contents: insertion sort, quicksort, heapsort, mergesort, shell sort, lower bounds, external sorting, sorting networks, sorting on mesh-connected processor arrays, sorting contest. Explanations are followed by source code.

### Algorithms for Programmers: Ideas and Source Code

by Jorg Arndt, 2008

Aimed at programmers who are interested in the selected algorithms and those who want to create optimized code. It covers low-level algorithms, combinatorial generation, fast orthogonal transforms, fast arithmetic, and algorithms for finite fields.

### Structure and Interpretation of Computer Programs

by Harold Abelson, Gerald Jay Sussman, Julie Sussman

Our goal is that student who complete this subject should have a good feel for the elements of style and the aesthetics of programming. They should have command of the major techniques for controlling complexity in a large system.

### Clever Algorithms

by Jason Brownlee

Implementing an Artificial Intelligence algorithm is difficult. Algorithm descriptions may be incomplete, inconsistent, and distributed across a number of papers, chapters and even websites. This can result in varied interpretations of algorithms, undue attrition of algorithms, and ultimately bad science

### Open Data Structures: An Introduction

by Pat Morin – AU Press, 2013

Offered as an introduction to the field of data structures and algorithms, the book covers the implementation and analysis of data structures for sequences (lists), queues, priority queues, unordered dictionaries, ordered dictionaries, and graphs.

### Search Algorithms and Applications

by Nashat Mansour – InTech, 2011

This book demonstrates the applicability of search algorithms for the purpose of developing solutions to problems that arise in a variety of domains. It is targeted to a wide group of readers: researchers, graduate students, and practitioners.

### Vector Models for Data-Parallel Computing

by Guy Blelloch – The MIT Press, 1990

Vector Models for Data-Parallel Computing describes a model of parallelism that extends and formalizes the Data-Parallel model on which the Connection Machine and other supercomputers are based. It presents many algorithms based on the model.

### Efficient Algorithms for Sorting and Synchronization

by Andrew Tridgell – samba.org, 1999

This thesis presents efficient algorithms for parallel sorting and remote data update. The sorting algorithms approach the problem by concentrating first on efficient but incorrect algorithms followed by a cleanup phase that completes the sort.

### An Introduction to the Analysis of Algorithms, 2nd Edition

The authors have drawn from both classical mathematics and computer science, integrating discrete mathematics, elementary real analysis, combinatorics, algorithms, and data structures.

### Real-World Applications of Genetic Algorithms

by Olympia Roeva

This book presents hybrid techniques based on Artificial Neural Network, Fuzzy Sets, Automata Theory, other metaheuristic or classical algorithms, etc. It examines various examples of algorithms in different real-world application domains.

### Algorithms by Robert Sedgewick, Kevin Wayne

by – Addison-Wesley Professional, 2011

This textbook surveys the most important algorithms and data structures in use today. Applications to science, engineering, and industry are a key feature of the text. We motivate each algorithm by examining its impact on specific applications.

### Algorithms and Data Structures: The Basic

### Toolbox

by K. Mehlhorn, P. Sanders – Springer, 2008

This book is a concise introduction addressed to students and professionals familiar with programming and basic mathematical language. Individual chapters cover arrays and linked lists, hash tables and associative arrays, sorting, and selection, etc

### Knapsack Problems: Algorithms and Computer Implementations

by Silvano Martello, Paolo Toth – John Wiley & Sons, 1990

The book on exact and approximate algorithms for a number of important problems in the field of integer linear programming, which the authors refer to as ‘knapsack’. Includes knapsack problems such as binary, bounded, unbounded or binary multiple.

### Planning Algorithms

by Steven M. LaValle

This is the only book for teaching and referencing of Planning Algorithms in applications including robotics, computational biology, computer graphics, manufacturing, aerospace applications, and medicine, etc.

### Algorithms and Data Structures

by Niklaus Wirth – Prentice Hall, 1985

The book treats practically important algorithms and data structures. It starts with a chapter on a data structure, then it treats sorting algorithms, concentrates on several examples of recursion, and deals with dynamic data structures.

### Tabu Search

by Wassim Jaziri – InTech, 2008

Tabu search is a mathematical optimization method. The goal of the book is to report original researchers on algorithms and applications of Tabu Search to real-world problems as well as recent improvements and extensions on its concepts and algorithms.

### Greedy Algorithms

by Witold Bednorz – InTech, 2008

Each chapter comprises a separate study on some optimization problem giving both an introductory look into the theory the problem comes from and some new developments invented by authors. Usually, some elementary knowledge is assumed.

### Algorithms

by Jeff Erickson – the University of Illinois at Urbana-Champaign, 2009

These are lecture notes, homework questions, and exam questions from algorithms courses the author taught at the University of Illinois. It is assumed that the reader has mastered the material covered in the first 2 years of a typical CS curriculum.

### Problems on Algorithms, 2nd edition

by Ian Parberry, William Gasarch – Prentice Hall, 2002

A collection of problems on the design, analysis, and verification of algorithms for practicing programmers who wish to hone and expand their skills, as a supplementary text for students, and as a self-study text for graduate students.

### Combinatorial Algorithms

by Albert Nijenhuis, Herbert S. Wilf – Academic Press Inc, 1978

This is a collection of mathematical algorithms with many new and interesting examples in this second edition. The authors tried to place in the reader’s hands a kit of building blocks with which the reader can construct more elaborate structures.

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**Top 10 Books and Resources to Become a Great Programmer**