David West

Gary Pollice

Brett McLaughlin

Provides information on analyzing, designing, and writing object-oriented software.

A Brain Friendly Guide to OOA&D

Head First Object-Oriented Analysis and Design

George T. Heineman

Stanley Selkow

Creating robust software requires the use of efficient algorithms, but programmers seldom think about them until a problem occurs. Algorithms in a Nutshell describes a large number of existing algorithms for solving a variety of problems, and helps you select and implement the right algorithm for your needs -- with just enough math to let you understand and analyze algorithm performance. With its focus on application, rather than theory, this book provides efficient code solutions in several programming languages that you can easily adapt to a specific project. Each major algorithm is presented in the style of a design pattern that includes information to help you understand why and when the algorithm is appropriate. With this book, you will: Solve a particular coding problem or improve on the performance of an existing solution Quickly locate algorithms that relate to the problems you want to solve, and determine why a particular algorithm is the right one to use Get algorithmic solutions in C, C++, Java, and Ruby with implementation tips Learn the expected performance of an algorithm, and the conditions it needs to perform at its best Discover the impact that similar design decisions have on different algorithms Learn advanced data structures to improve the efficiency of algorithms With Algorithms in a Nutshell, you'll learn how to improve the performance of key algorithms essential for the success of your software applications.

Algorithms in a Nutshell

I highly recommend this book for anyone who's ever tried to implement RUP on a small project. Pollice and company have demystified and effectively scaled the process while ensuring that its essence hasn't been compromised. A must-have for any RUPster's library! Chris Soskin, Process Engineering Consultant, Toyota Motor SalesDo you want to improve the process on your next project? Perhaps you'd like to combine the best practices from the Rational Unified Process (RUP) and from agile methodologies (such as Extreme Programming). If so, buy this book! Software Development for Small Teams describes an entire software development project, from the initial customer contact through delivery of the software. Through a case study, it describes how one small, distributed team designed and applied a successful process. But this is not a perfect case study. The story includes what worked and what didn't, and describes how the team might change its process for the next project. The authors encourage you to assess their results and to use the lessons learned on your next project. Key topics covered include: Achieving a balance between people, process, and tools; recognizing that software develo

A RUP-centric Approach

Software Development for Small Teams

Creating robust software requires the use of efficient algorithms, but programmers seldom think about them until a problem occurs. This updated edition of Algorithms in a Nutshell describes a large number of existing algorithms for solving a variety of problems, and helps you select and implement the right algorithm for your needs—with just enough math to let you understand and analyze algorithm performance. With its focus on application, rather than theory, this book provides efficient code solutions in several programming languages that you can easily adapt to a specific project. Each major algorithm is presented in the style of a design pattern that includes information to help you understand why and when the algorithm is appropriate. With this book, you will: Solve a particular coding problem or improve on the performance of an existing solution Quickly locate algorithms that relate to the problems you want to solve, and determine why a particular algorithm is the right one to use Get algorithmic solutions in C, C++, Java, and Ruby with implementation tips Learn the expected performance of an algorithm, and the conditions it needs to perform at its best Discover the impact that similar design decisions have on different algorithms Learn advanced data structures to improve the efficiency of algorithms

Gary Pollice

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