Product Description

Often referred to as the "black art" because of its complexity and uncertainty, software estimation is not as hard or mysterious as people think. However, the art of how to create effective cost and schedule estimates has not been very well publicized. While the average software organization can struggle with project costs that run double their original estimates, some of the more sophisticated organizations achieve results with estimation errors as low as 5-10%. These best-in-class organizations use scientific techniques that are not cost-effective, however, making them of limited use to most software development organizations. To address these issues, Software Estimation focuses on the art of software estimation and provides a proven set of procedures and heuristics that software developers, technical leads, and project managers can apply to their projects. Instead of arcane treatises and rigid modeling techniques, award-winning author Steve McConnell gives practical guidance to help organizations achieve basic estimation proficiency and lay the groundwork to continue improving project cost estimates. This book is organized from simple tips to more advanced ideas; it does not avoid the more hairy mathematical estimation approaches, but the non-mathematical reader will find plenty of useful guidelines without getting bogged down in complex formulas.

Product Details

• Amazon Sales Rank: #5809 in Books
• Published on: 2006-03-01
• Number of items: 1
• Binding: Paperback
• 308 pages

From the Publisher
Unlike other books that focus exclusively on the science of estimation—including rigid modeling techniques and continuous feedback loops that are not cost effective to most organizations—this unique guide offers practical, tested, hands-on advice for estimating software development costs in the real world. It is written by the award-winning author of Code Complete.

Key Book Benefits:

Delivers practical insights about a critical subject too-often obscured by academic jargon Two-color graphics present mathematical information in an easy-to-understand format Provides specific practices that can be used immediately by any software development organization Features numerous, to-the-point tips about the estimation process, as well as individual steps to creating successful estimates

About the Author
Steve McConnell is recognized as one of the premier authors and voices in the development community. He is Chief Software Engineer of Construx Software and the award-winning author of Code Complete and Rapid Development, both honored with Software Development magazine's Jolt Award for product excellence; Software Project Survival Guide; and Professional Software Development.

Customer Reviews

Excellent software engineering book backed up by solid empirical studies
Honesty, I was expecting very "soft" content, i.e., pages spent over-analyzing obvious points and so on. BUT this description could not be farther from the truth. In Software Estimation, McConnell draws on over a hundred published studies on the topic of software estimation as well as numerous case studies. The book is data driven and based on statistical techniques. McConnell emphases counting concrete project steps and comparing them with previous estimates where as intuiting off-the-cuff estimates is a major no-no.

Good Primer to start with
I have just completed the reading. Not that, I didn't know estimation, nor that I was struggling to do a right kind of estimation. I am already fairly accustomed with standard tools and techniques in the world of professional software estimation. What I found appealing in this book is the approach towards estimation at the start.

Today, I was sitting in an informal discussion session with a bunch of college graduates who barely completed 1 year in this industry. It was an open discussion set, and one point came up on right estimation. Many of them had gone through 20 hour workday regimen during the difficult times of the project, and all of them were convinced that somebody did not do the estimation right. To explain that estimation is not that easy math work like a college paper, I started with a quiz: What's the latitude of Sanghai. And as I continued speaking on estimating the latitude of Sanghai, I found increasing number of approving nods all around the room. Happy me! It was not always the case where I found an immediate place to apply my book reading in past, that too with the nods of approval.

Coming back to the book, I will definitely recommend this book to all software project leaders and project managers to get a feel of the subject and how to address the problem at large. To gain deeper knowledge there are tons of research papers and books waiting for you, but if you are a busy professional, go through this book first.

A Must Have Resource
Basic premise: that "the goal is software estimation is not pinpoint accuracy but estimates that are accurate enough to support effective project control. To that end, a "good estimate" is one that "provides a clear enough view of the project reality to allow the project leadership to make good decisions about how to control the project to hit its targets."

Software estimation is inherently nontrivial. The resulting product is virtually invisible until it is finished---and you rarely end up with the same product that you initially estimated anyway. Early on, requirements are difficult to state (and measure) precisely, and as Rittel stated "the true nature of the problem only emerges as a solution is developed."

Many PM's still believe that estimates are based on multiples of a gut feel. However, the ambiguous nature of software reality requires multiple and varied quantitative methods just to define the estimate space in terms of order of magnitude.

This book provides a basic and superficial description of a number of these methods, including how and when to best apply them. It is an excellent primer to reading other more exhaustive texts (such as Stutzke's Estimating Software-Intensive Systems) and an indispensable desk-reference for Program Managers, Project Managers and Parametricians. Highly recommended.