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Many software projects fail because their leaders don't know how to estimate, schedule, or measure them accurately. Fortunately, proven tools and techniques exist for every facet of software estimation. Estimating Software-Intensive Systems brings them together in a real-world guidebook that will help software managers, engineers, and customers immediately improve their estimatesand drive continuing improvements over time.
Dick Stutzke presents here a disciplined and repeatable process that can produce accurate and complete
estimates for any project, product, or process, no matter how new or unusual. Stutzke doesn't just describe formal techniques: He offers simple, easy-to-use templates, spreadsheets, and tools you can start using today to identify and estimate product size, performance, and qualityas well as project cost, schedule, and risk reserves.
Stutzke shows how to quickly "get your arms around" users' problems and requirements, the structure of a solution, and the process needed to deliver it. You'll learn how to choose the most appropriate estimating techniques and tools; collect accurate data, track progress, and update estimates; and recalibrate estimating models to improve estimation accuracy.
Stutzke's techniques apply whether you're creating custom in-house business software, purchasing or customizing "off-the-shelf" technology, or constructing complex, one-of-a-kind military, industrial, or commercial systems. These techniques apply to small and large projects, and to all project life cyclesfrom agile to plan-driven. This book will help you plan, estimate, budget, schedule, purchase, design, build, test, deploy, operate, and maintain software-intensive systems. It explains how to size software, identify all cost components, calculate the associated costs, and set a competitive price.
A separate section covers topics of interest for large projects: designing an appropriate work breakdown structure, collecting data from cost accounting systems, and using earned value measurement.
An accompanying CD-ROM contains templates, supplemental notes, and Microsoft Excel spreadsheets to estimate and track projects, product characteristics, and processes. It contains an extensive bibliography and links to web resources on software estimation, measurement, and related topics. You'll find updates and even more information on this book's companion web site, http://www.sw-estimation.com.
© Copyright Pearson Education. All rights reserved.
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Chapter related to this title.
About the Author.
I. The Essentials.
Reasons to Estimate and Measure.
Specific Quantities to Estimate and Measure.
The Nature of Estimation.
Why Software Is Especially Hard to Estimate.
A Practical Approach.
2. Planning a Warehouse Inventory System.
Warehouse Inventory Management System.
Recording the Information.
Discussion of the Example.
Doing Better: A Planning Workbook.
3. A Basic Estimating Process: The Linear Method.
Criteria for “Good” Estimates.
Types of Resources.
The Linear Method: A Simple Process.
Using the Linear Method.
Documenting Your Estimates.
Managing Your Information.
4. Measurement and Estimation.
Reasons to Measure.
Measuring Size and Productivity (Direct and Indirect Measures).
Criteria for “Good” Measures.
Choosing Useful Measures.
5. Estimating Techniques.
Expert Judgment: The Delphi Technique.
Additive and Multiplicative Analogies.
Program Evaluation and Review Technique (PERT).
An Example: Using PERT Values.
Using the PERT Values to Estimate Risk Reserve.
Algorithmic Analogy Estimation.
6. Estimating Annual Maintenance Costs.
The Maintenance Process.
Building the Estimation Model.
Calibrating the Model.
Tracking and Updating.
Improving the Estimation Model.
II. THE DETAILS.
7. Preparing to Estimate (Precursors of Estimation).
The Precursors of Estimation.
How to Understand the Overall Job: The Key Diagrams.
The Operational Concept.
Identifying Products and Services.
Project Goals and Constraints.
8. Estimating Software Size: The Basics.
The Sizing Process.
Example: Using the Operational Concept.
Accounting for Size Growth and Volatility.
9. Estimating Software Size: The Details.
UML-Based Sizing and Use Case Points.
Web Objects and Internet Points.
Simplified Ways to Count Function Points.
Object-Oriented Size Measures.
Defining Source Lines of Code (SLOC).
Estimating New Code.
Sizing Reused Source Code.
“Sizing” Commercial Off-the-Shelf Software Components.
The COCOTS Model.
10. Production Processes (Project Life Cycles).
Elements of a Project Life Cycle Model.
The Spectrum of Software Life Cycles.
Choosing an Appropriate Project Life Cycle.
Extending the Basic Development Life Cycle Models.
Production and Delivery Activities.
11. Bottom-Up Estimating and Scheduling.
Summary of the Process.
The Work Breakdown Structure.
Creating Your WBS.
Building the Network: Cards on the Wall Method.
12. Top-Down Estimating and Allocation.
Relating Effort, Duration, and Staffing.
Planned Versus Actual Availability.
Allocating Effort and Time.
13. Parametric Models.
Types of Parametric Models.
Core Effort and Schedule.
A Simple Parametric Model.
Adding Missing Phases and Activities.
Adjusting for Different Characteristics.
Handling Size, Cost, and Schedule Constraints.
Evaluating a Hardware/Software Trade.
Calibrating Parametric Models.
Parametric Models for Hardware Costs.
Selecting an Automated Estimation Tool.
Helping Nonestimators Provide Good Parameter Values.
14. Estimating Risk Reserves.
The Risk Management Process.
Identifying Risks and Mitigation Actions.
Analyzing and Prioritizing Risks: Risk Impact.
Calculating the Risk Reserve.
Planning: Deciding to Defer Mitigation Tasks.
Tracking and Updating.
15. Calculating Cost and Price: The Basics.
Direct and Indirect Costs.
Calculating Direct Costs.
Calculating Indirect Costs.
Profit and the “Fee Rate”.
Calculating the Loaded Cost.
Cash Flow and Interest Costs.
Determining the Selling Price for a Product6.
Evaluating the Total Ownership Cost.
Evaluating a Product or Project.
Reducing the Cost or Price.
The Need for Multiple Models.
III. CLOSING THE FEEDBACK LOOP.
16. Collecting Data: Basics.
Why Should You Even Collect Historical Data?
Data Collection Templates.
Automating Data Collection and Analysis.
Collecting Effort and Cost Data.
17. Tracking Status.
Tracking Test Status.
Tracking Size and Productivity.
Tracking Size with Error Bars.
Other Ways to Detect Trouble.
18. Updating Estimates.
Reasons to Update Estimates.
The Basic Process.
When to Prepare Updated Estimates.
Preparing Updated Estimates.
Preparing an Estimate to Complete.
19. Consolidating and Applying Your Knowledge.
Review of Estimation and Measurement.
Implementing Estimation and Measurement.
Defining an Estimation Process.
Establishing an Integrated Estimation Process.
Addressing New Technologies and Processes.
IV. HANDLING LARGE PROJECTS.
20. Crafting a WBS.
The Work Breakdown Structure: Additional Concepts.
A Generic WBS (HW, SW, Data, Services).
Examples of Alternate Partitioning.
Customizing Your WBS.
21. Earned Value Measurement.
Assessing Overall Project Status.
Converting Schedule Variance to Time.
Earned Value Example.
Prediction Completion Costs.
22. Collecting Data: Details.
Project Tracking Systems.
Time Reporting and Cost Accounting Systems.
Defining “Good” Charge Numbers.
Limitations of Accounting Systems.
Tracking Heterogeneous Project Teams.
Tracking IDIQ Contracts.
23. Calculating Costs and Bid Price.
Review of Direct and Indirect Costs.
Rate Types for U.S. Government Contracts.
Financial Risks of U.S. Government Contracts.
Calculating a Bid Price.
Cash Flow and Interest Costs.
Setting a Bid Price.
Reducing the Price.
V. ESTIMATING PRODUCTS AND PROCESSES.
24. Determining Product Performance.
Types of Product Performance.
Estimating and Measuring Software Performance.
Rough Order of Magnitude Calculations.
The Resource Usage Matrix.
Modeling Web-Based Systems.
Choosing a Technique.
Performance Engineering Process.
Estimating Costs for Performance Engineering.
25. Determining Product Quality.
Why Product Quality Is Important.
Determining Quality During a Project.
Estimating Defects During Design and Construction.
Measuring Defects During Testing.
Estimating Software Reliability.
Measuring Defects Using Capture/Recapture.
Observing Defects During Actual Use.
Closing the Loop.
Internal Measures of Software Quality.
Measures of Document Quality.
26. Measuring and Estimating Process Performance.
Defining a Process.
Controlling Production Processes.
Measuring Process Performance.
Measuring the Cost of Quality.
Predicting Process Performance.
Statistical Process Control.
Staged Defect Removal Models.
Building Process Performance Models.
27. Ranking and Selecting Items.
A Technique to Handle Two Criteria.
Techniques to Handle Multiple Criteria.
Multi-Attribute Utility Theory (MAUT).
The Analytic Hierarchy Process.
Estimating Module Size Using AHP.
Appendix A: Roles and Responsibilities for Estimation.
Appendix B: Measurement Theory and Statistics.
Measurement and Scale Types.
Statistics and Scale Types.
Appendix C: Measures of Estimation Accuracy.
Statistics of a Set of Estimates.
Statistics of a Time Sequence of Estimates.
Choosing the “Best” Measure of Estimation Accuracy.
Using Excel to Calculate Estimation Error.
Appendix D: Summation Formulas for Series.
Appendix E: Excel for Estimators.
Labeling Spreadsheets and Documents.
Macros and Visual Basic for Applications.
Projects to develop and maintain software-intensive systems can involve the following:
Practitioners who develop, manage, procure, or operate software-intensive systems need to estimate and measure the resources needed to perform such activities. They also need to calculate costs, set bid prices, and evaluate cost and price. Some practitioners also need to estimate and measure the usage of computer resources, product quality (defects), and the effectiveness and efficiency of production processes.
You can use computer-based tools to generate an estimate in a few minutes. Remember, however, that estimation is more than clever techniques, parametric models, and tools however. The greatest challenge for an estimator is deciding where to start when faced with a blank sheet of paper. For example, during a proposal, engineers, managers, planners, and estimators must quickly gain an understanding of the user's problem and requirements, the structure of the solution, and the process needed to design, build, and deliver that solution.
This book describes ways to help readers quickly "get their arms around" a product or system that they have never seen before. It also provides guidance on selecting appropriate estimating techniques and tools based on the type of resource and project phase.
This book discusses measurement and data collection so that readers can obtain accurate data to track progress, prepare updated estimates, and calibrate estimating models. For example, it describes different measures of software size, including use case points, function points, and source lines of code. The book describes earned value measurement and provides practical suggestions to address the particular needs of large projects related to status tracking and cost accounting.
This book covers a wide range of topics and techniques. To help you quickly find information, the book has 27 chapters, organized into five parts:
1. The Essentials
2. The Details
3. Closing the Feedback Loop
4. Handling Large Projects
5. Estimating Products and Processes
This book is relevant to both small and large projects using either agile or plan-driven production processes. Much of the material applies to criteria in process maturity models and to earned value measurement. The book also addresses internal Information Technology applications, mass market shrink-wrapped products, and complex systems.
Various individuals reviewed parts of the book and provided valuable comments. Early reviewers included Wolf Goethert, Harry Delugach, Steve Tockey, Brad Tyler, Chuck Connell, and Gary Thomas. Kathy Hedges reviewed several early chapters and provided detailed suggestions. Reviewers of the first draft (May 2004) included Mike Tarrani, Tom McGibbon, Kelly Butler, Jim Brosseau, Ron Lichty, and two anonymous reviewers. Ron Lichty's 40 pages of detailed comments were especially helpful, and led to a restructuring of the book. Dick Fitzer of SAIC reviewed the final manuscript.
Peter Gordon, my editor at Pearson Education, guided me, provided sage advice, and never lost hope over the many years it took to produce this book. (Thanks to Anita Carleton and Kim Caputo for recommending Peter.) The Pearson Education production staff in Boston and Indianapolis completed a lot of quality work in a short time.
Many SAIC employees shared their knowledge as we worked together on various proposals and projects. Certain individuals deserve special mention. Tony Jordano sponsored the development and update of SAIC's estimating courses over the years, which provided me the opportunity to test and hone my ideas. Rod Roberts provided encouragement and support throughout the project. Ken Powers provided tips on using Microsoft Office and helped debug VBA macros on numerous occasions. Mary Ellen Harris promptly obtained numerous reprints and researched obscure citations. The Redstone Scientific Information Center provided access to technical books and journals.
Most importantly, I would like to thank my indispensable assistant, Sue Totten. Sue prepared charts for SAIC's estimating courses, my conference presentations, and technical reports. She formatted numerous drafts of this book and prepared many of the original line drawings. She suggested improvements to the book and to our processes. Sue maintained configuration control over the many drafts of courses, papers, and book chapters. She worked late on many days, and asked what she could do next to help. She acted as my alter ego, handling many routine duties so I had more time to write. Throughout the entire ordeal, Sue retained her sense of humor. (At one point, I thought I would have to rename the book Unser Kampf.) Sue, I could not have done it without you!
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