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Software Engineering Economics, by Barry W. Boehm

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Software Engineering Economics is an invaluable guide to determining software costs, applying the fundamental concepts of microeconomics to software engineering, and utilizing economic analysis in software engineering decision making.
- Sales Rank: #122757 in Books
- Published on: 1981-11-01
- Original language: English
- Number of items: 1
- Dimensions: 9.10" h x 1.60" w x 6.90" l, 2.82 pounds
- Binding: Paperback
- 767 pages
About the Author
Boehm, together with his colleagues at the University of Southern California's Center for Software Engineering, he continues as a leader in software cost estimation.
Most helpful customer reviews
14 of 15 people found the following review helpful.
A great classic. Needs to be updated for modern practices.
By Ted Carroll (revonrat@nwlink.com)
This is a great book and should be required reading for anyone who schedules software projects. Some of the data is out of date and readers should look to the website for updates. If this book contained current information it would easily be a 10.
14 of 16 people found the following review helpful.
A classic "must read" - but be aware of its limitations
By Ramon
"Software Engineering Economics" is *the* book to be considered for anybody wishing to seriously enter the world of software cost estimation - only if it were because of the extremely great influence this book has had on this very peculiar aspect of software engineering. In this aspect, Barry Boehm is undoubtly the master.
HOWEVER, it must be kept in mind that the book itself is somewhat outdated - COCOMO 81, as defined by Barry Boehm, has been overtaken by new technologies and in particular by the surge in PCs & the Internet. The basic model is still valid - I still use it myself - provided you are aware what the background in computing was when it was written, and you carefully assign the adjustment factors.
Barry Boehm himself recognizes that COCOMO 81 is no longer valid - hence his collaboration with COCOMO II, which has addressed many of the problems that affected the old COCOMO 81 (e.g., it was mainly thought for development of software on expensive mainframes, and development tools have greatly evolved since that time). Still, I insist, if you are careful when making your estimations, the model and the techniques presented in this book are very useful and could be applied even on more modern projects.
My second HOWEVER is related to use the model presented in this book for Software Maintenance purposes. Though the book has a chapter on this issue, by opinion is a radical NO-No on this particular issue. COCOMO 81 (as presented in this book) and COCOMO II are adequate for software development purposes. I totally disagree that they are adequate for software Maintenance purposes (though COCOMO II is at least not so very bad). Apart from the fact that it ignores things such as regression testing, or the number of releases to be made during such maintenance, it also ignores the fact that software "degrades" during such maintenance - subsequent modifications introduce more and more stress on the original design, until at a certain moment the software requires a great "overhaul" in order to solve a lot of patchwork that has accumulated over the years. Hence the typical case of having to redesign a complete new software system because maintenance of the old system becomes too expensive.
In any case, if aware of such limitations, I can highly recommend it.
9 of 12 people found the following review helpful.
Economic analysis of software decisions making
By Daniel Mall
A classic reference on estimating the cost of software projects, economic analysis techniques, and applying economic principals to upper-level management of software projects. The intimidating appearance of the text on initial inspection is overcome by the author's excellent organization of the content into small chapters and his lucid writing style. The definition of a software cost model called the constructive cost model (COCOMO) is a major centerpiece. Another centerpiece is the chapters on cost-effectiveness analysis, multiple goal decision analysis, dealing with uncertainties and the value of information, software project planning and control, and improving software productivity. Alternatives to cost models such as experts, analogy, Parkinson, price-to-win, top-down, and bottom-up are discussed in Chapter 22. Uses several case studies for example a transaction processing system. Contains an excellent set of questions and exercises at the end of each chapter.
The COCOMO model is calibrated by industry data and expert opinion. Given module size estimates in lines of code as input the COCOMO model will predict effort and schedule in man-months. The COCOMO predictions cover the plans, product design, programming, and integration & test portions of the life cycle. The validity of the model is illustrated by charting actual vs. COCOMO prediction and the detailed analysis of the COCOMO cost driver attributes in Chapters 24-26. Product attributes are required software reliability (RELY), data base size (DATA), and product complexity (CPLX). Computer attributes are execution time constraint (TIME), main storage constraint (STOR), virtual machine volatility (VIRT), and computer turnaround time (TURN). Personnel attributes are analyst capability (ACAP), applications experience (AEXP), programmer capability (PCAP), virtual machine experience (VEXP), and programming language experience (LEXP). Project attributes are modern programming practices (MODP), use of software tools (TOOL), and required development schedule (SCED).
Readers should be aware that some aspects of the COCOMO have been replaced by the publication of the "Software Cost Estimation with COCOMO II" book. The "COCOMO II" book contains a preface section titled "Relation to 1981 Software Engineering Book". I recommend keeping a copy of this preface handy while you read "Software Engineering Economics" because it provides a chapter-by-chapter assessment of the relevance of the "Software Engineering Economics" content in the year 2000.
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