Binding: Paperback Dewey Decimal Number: 005.1 EAN: 9780735605350 ISBN: 0735605351 Label: Microsoft Press Manufacturer: Microsoft Press Number Of Items: 1 Number Of Pages: 308 Publication Date: March 01, 2006 Publisher: Microsoft Press Sales Rank: 17551 Studio: Microsoft Press
Product DescriptionOften 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.
Customer Reviews
Average Rating:
Rating: - Science of software estimation
Steve McConnell explains how software estimation is more a science than an art. Information in this books can applied to agile development as well to the classical approach. So if You struggle (I'm sure You do) with estimation, this is excellent book for You, it doesn't matter whether You are a developer or a manager.
Rating: - 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 ... Read More
Rating: - 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 ... Read More
Rating: - 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 ... Read More
Rating: - Eye Opening
Despite the fact that most software developers consider themselves engineers or scientists, many mainly rely upon gut instinct for estimation rather than data. The material in this book enabled me to persuade my developers of the limits of gut instinct, to guide them to develop more quantitative methods and to help them predict the precision of their estimates.
- Science of software estimation
- Excellent software engineering book backed up by solid empirical studies
