Software Measurement and Estimation A Practical Approach,9780471676225

Software Measurement and Estimation A Practical Approach

by ;
Edition: 1st
ISBN13: 9780471676225
ISBN10: 0471676225
Format: Hardcover
Pub. Date: 2006-06-05
Publisher(s): Wiley-IEEE Computer Society Pr
  • Free Shipping Icon

    This Item Qualifies for Free Shipping!*

    *Excludes marketplace orders.

List Price: $161.22

Buy New

Arriving Soon. Will ship when available.
$153.54
Add to Cart

Buy Used

Arriving Soon. Will ship when available.
$115.16
Add to Cart

Rent Textbook

Select for Price
Add to Cart
There was a problem. Please try again later.

eTextbook

We're Sorry
Not Available

Buy from our Marketplace starting at $3.91

How Marketplace Works:

  • This item is offered by an independent seller and not shipped from our warehouse
  • Item details like edition and cover design may differ from our description; see seller's comments before ordering.
  • Sellers much confirm and ship within two business days; otherwise, the order will be cancelled and refunded.
  • Marketplace purchases cannot be returned to eCampus.com. Contact the seller directly for inquiries; if no response within two days, contact customer service.
  • Additional shipping costs apply to Marketplace purchases. Review shipping costs at checkout.

Summary

This book serves as a practical guide to metrics and quantitative software estimation Begins with the foundations of measurement and metrics, and then focuses on techniques and tools for estimation of the required effort and the resulting quality of a software project Addresses how software effort estimation can be used to create more accurate estimates, justify estimates based on data, decrease the risks of missing deadlines and cost targets, plus more Numerous examples illustrate how to use the tools and methodologies to solve real problems

Author Biography

LINDA M. LAIRD is Adjunct Professor at Stevens Institute of Technology, where she teaches Quantitative Software Engineering. Dr. Laird has more than thirty years of experience building and managing systems for Lucent Technologies, AT&T, and Bell Laboratories.

M. CAROL BRENNAN is former vice president and general manager of the Quality and Operations Center at Telcordia Technologies, where she was responsible for design, development, and implementation of the Telcordia quality management system. She has more than twenty-five years of experience in software design, development, testing, performance, maintenance, and customer support as well as quality strategy, policy, and implementation.

Table of Contents

Acknowledgments xv
1. Introduction
1(6)
1.1 Objective
1(1)
1.2 Approach
2(1)
1.3 Motivation
3(2)
1.4 Summary
5(1)
References
6(1)
2. What to Measure
7(8)
2.1 Method 1: The Goal Question Metrics Approach
9(1)
2.2 Method 2: Decision Maker Model
10(1)
2.3 Method 3: Standards Driven Metrics
10(1)
2.4 Extension to GQM: Metrics Mechanism
11(1)
2.5 What to Measure Is a Function of Time
12(1)
2.6 Summary
12(1)
Problems
13(1)
Project
13(1)
References
13(2)
3. Measurement Fundamentals
15(19)
3.1 Initial Measurement Exercise
15(1)
3.2 The Challenge of Measurement
16(1)
3.3 Measurement Models
16(4)
3.3.1 Text Models
16(2)
3.3.2 Diagrammatic Models
18(1)
3.3.3 Algorithmic Models
18(1)
3.3.4 Model Examples: Response Time
18(1)
3.3.5 The Pantometric Paradigm: How to Measure Anything
19(1)
3.4 Meta-Model for Metrics
20(1)
3.5 The Power of Measurement
21(1)
3.6 Measurement Theory
22(8)
3.6.1 Introduction to Measurement Theory
22(1)
3.6.2 Measurement Scales
23(1)
3.6.3 Measures of Central Tendency and Variability
24(4)
3.6.3.1 Measures of Central Tendency
25(1)
3.6.3.2 Measures of Variability
25(2)
3.6.4 Validity and Reliability of Measurement
27(1)
3.6.5 Measurement Error
28(2)
3.7 Accuracy Versus Precision and the Limits of Software Metrics
30(1)
3.8 Summary
31(1)
Problems
31(2)
Projects
33(1)
References
33(1)
4. Measuring Size
34(20)
4.1 Physical Measurements of Software
34(6)
4.1.1 Measuring Lines of Code
35(1)
4.1.2 Language Productivity Factor
35(2)
4.1.3 Counting Reused and Refactored Code
37(2)
4.1.4 Counting Nonprocedural Code Length
39(1)
4.1.5 Measuring the Length of Specifications and Design
39(1)
4.2 Measuring Functionality
40(11)
4.2.1 Function Points
41(9)
4.2.1.1 Counting Function Points
41(4)
4.2.1.2 Function Point Example
45(2)
4.2.1.3 Converting Function Points to Physical Size
47(1)
4.2.1.4 Converting Function Points to Effort
47(1)
4.2.1.5 Other Function Point Engineering Rules
48(1)
4.2.1.6 Function Point Pros and Cons
49(1)
4.2.2 Feature Points
50(1)
4.3 Summary
51(1)
Problems
51(1)
Project
52(1)
References
53(1)
5. Measuring Complexity
54(25)
5.1 Structural Complexity
55(18)
5.1.1 Size as a Complexity Measure
55(3)
5.1.1.1 System Size and Complexity
55(1)
5.1.1.2 Module Size and Complexity
56(2)
5.1.2 Cyclomatic Complexity
58(5)
5.1.3 Halstead's Metrics
63(2)
5.1.4 Information Flow Metrics
65(2)
5.1.5 System Complexity
67(4)
5.1.5.1 Maintainability Index
67(2)
5.1.5.2 The Agresti–Card System Complexity Metric
69(2)
5.1.6 Object-Oriented Design Metrics
71(2)
5.1.7 Structural Complexity Summary
73(1)
5.2 Conceptual Complexity
73(1)
5.3 Computational Complexity
74(1)
5.4 Summary
75(1)
Problems
75(2)
Projects
77(1)
References
78(1)
6. Estimating Effort
79(39)
6.1 Effort Estimation: Where Are We?
80(1)
6.2 Software Estimation Methodologies and Models
81(26)
6.2.1 Expert Estimation
82(3)
6.2.1.1 Work and Activity Decomposition
82(1)
6.2.1.2 System Decomposition
83(1)
6.2.1.3 The Delphi Methods
84(1)
6.2.2 Using Benchmark Size Data
85(3)
6.2.2.1 Lines of Code Benchmark Data
85(2)
6.2.2.2 Function Point Benchmark Data
87(1)
6.2.3 Estimation by Analogy
88(3)
6.2.3.1 Traditional Analogy Approach
89(2)
6.2.3.2 Analogy Summary
91(1)
6.2.4 Proxy Point Estimation Methods
91(10)
6.2.4.1 Meta-Model for Effort Estimation
91(1)
6.2.4.2 Function Points
92(2)
6.2.4.3 Object Points
94(1)
6.2.4.4 Use Case Sizing Methodologies
95(6)
6.2.5 Custom Models
101(2)
6.2.6 Algorithmic Models
103(5)
6.2.6.1 Manual Models
103(2)
6.2.6.2 Estimating Project Duration
105(1)
6.2.6.3 Tool-Based Models
105(2)
6.3 Combining Estimates
107(1)
6.4 Estimating Issues
108(4)
6.4.1 Targets Versus Estimates
108(1)
6.4.2 The Limitations of Estimation: Why?
109(1)
6.4.3 Estimate Uncertainties
109(3)
6.5 Estimating Early and Often
112(1)
6.6 Summary
113(1)
Problems
114(2)
Projects
116(1)
References
116(2)
7. In Praise of Defects: Defects and Defect Metrics
118(26)
7.1 Why Study and Measure Defects?
118(1)
7.2 Faults Versus Failures
119(1)
7.3 Defect Dynamics and Behaviors
120(3)
7.3.1 Defect Arrival Rates
120(1)
7.3.2 Defects Versus Effort
120(1)
7.3.3 Defects Versus Staffing
120(1)
7.3.4 Defect Arrival Rates Versus Code Production Rate
121(1)
7.3.5 Defect Density Versus Module Complexity
122(1)
7.3.6 Defect Density Versus System Size
122(1)
7.4 Defect Projection Techniques and Models
123(10)
7.4.1 Dynamic Defect Models
123(6)
7.4.1.1 Rayleigh Models
124(3)
7.4.1.2 Exponential and S-Curves Arrival Distribution Models
127(1)
7.4.1.3 Empirical Data and Recommendations for Dynamic Models
128(1)
7.4.2 Static Defect Models
129(4)
7.4.2.1 Defect Insertion and Removal Model
129(1)
7.4.2.2 Defect Removal Efficiency: A Key Metric
130(2)
7.4.2.3 Static Defect Model Tools
132(1)
7.5 Additional Defect Benchmark Data
133(3)
7.5.1 Defect Data by Application Domain
133(1)
7.5.2 Cumulative Defect Removal Efficiency (DRE) Benchmark
134(1)
7.5.3 SEI Levels and Defect Relationships
134(1)
7.5.4 Latent Defects
135(1)
7.5.5 A Few Recommendations
135(1)
7.6 Cost Effectiveness of Defect Removal by Phase
136(1)
7.7 Defining and Using Simple Defect Metrics: An Example
136(3)
7.8 Some Paradoxical Patterns for Customer Reported Defects
139(1)
7.9 Answers to the Initial Questions
140(1)
7.10 Summary
140(1)
Problems
141(1)
Projects
142(1)
References
142(2)
8. Software Reliability Measurement and Prediction
144(23)
8.1 Why Study and Measure Software Reliability?
144(1)
8.2 What Is Reliability?
144(1)
8.3 Faults and Failures
145(1)
8.4 Failure Severity Classes
145(1)
8.5 Failure Intensity
146(1)
8.6 The Cost of Reliability
147(1)
8.7 Software Reliability Theory
148(4)
8.7.1 Uniform and Random Distributions
148(2)
8.7.2 The Probability of Failure During a Time Interval
150(1)
8.7.3 F(t): The Probability of Failure by Time T
151(1)
8.7.4 R(t): The Reliability Function
151(1)
8.7.5 Reliability Theory Summarized
152(1)
8.8 Reliability Models
152(3)
8.8.1 Types of Models
152(2)
8.8.2 Predicting Number of Defects Remaining
154(1)
8.9 Failure Arrival Rates
155(6)
8.9.1 Predicting Failure Arrival Rates Using Historical Data
155(1)
8.9.2 Engineering Rules for MTTF
156(1)
8.9.3 Musa's Algorithm
157(1)
8.9.4 Operational Profile Testing
158(3)
8.9.5 Predicting Reliability Summary
161(1)
8.10 But When Do I Ship?
161(1)
8.11 System Configurations: Probability and Reliability
161(2)
8.12 Answers to Initial Question
163(1)
8.13 Summary
164(1)
Problems
164(1)
Project
165(1)
References
166(1)
9. Response Time and Availability
167(14)
9.1 Response Time Measurements
168(2)
9.2 Availability
170(7)
9.2.1 Availability Factors
172(1)
9.2.2 Outage Scope
173(1)
9.2.3 Complexities in Measuring Availability
173(1)
9.2.4 Software Rejuvenation
174(14)
9.2.4.1 Software Aging
175(1)
9.2.4.2 Classification of Faults
175(1)
9.2.4.3 Software Rejuvenation Techniques
175(1)
9.2.4.4 Impact of Rejuvenation on Availability
176(1)
9.3 Summary
177(1)
Problems
178(1)
Project
179(1)
References
180(1)
10. Measuring Progress 181(16)
10.1 Project Milestones
182(3)
10.2 Code Integration
185(2)
10.3 Testing Progress
187(1)
10.4 Defects Discovery and Closure
188(4)
10.4.1 Defect Discovery
189(1)
10.4.2 Defect Closure
190(2)
10.5 Process Effectiveness
192(2)
10.6 Summary
194(1)
Problems
195(1)
Project
196(1)
References
196(1)
11. Outsourcing 197(11)
11.1 The "O" Word
197(1)
11.2 Defining Outsourcing
198(3)
11.3 Risk Management and Outsourcing
201(2)
11.4 Metrics and the Contract
203(3)
11.5 Summary
206(1)
Problems
206(1)
Projects
207(1)
References
207(1)
12. Financial Measures for the Software Engineer 208(23)
12.1 It's All About the Green
208(1)
12.2 Financial Concepts
209(1)
12.3 Building the Business Case
209(15)
12.3.1 Understanding Costs
210(6)
12.3.1.1 Salaries
210(1)
12.3.1.2 Overhead costs
210(1)
12.3.1.3 Risk Costs
211(2)
12.3.1.4 Capital Versus Expense
213(3)
12.3.2 Understanding Benefits
216(2)
12.3.3 Business Case Metrics
218(6)
12.3.3.1 Return on Investment
218(1)
12.3.3.2 Payback Period
219(1)
12.3.3.3 Cost/Benefit Ratio
220(1)
12.3.3.4 Profit and Loss Statement
221(1)
12.3.3.5 Cash Flow
222(1)
12.3.3.6 Expected Value
223(1)
12.4 Living the Business Case
224(1)
12.5 Summary
224(3)
Problems
227(1)
Projects
228(2)
References
230(1)
13. Benchmarking 231(7)
13.1 What Is Benchmarking?
231(1)
13.2 Why Benchmark?
232(1)
13.3 What to Benchmark
232(1)
13.4 Identifying and Obtaining a Benchmark
233(1)
13.5 Collecting Actual Data
233(1)
13.6 Taking Action
234(1)
13.7 Current Benchmarks
234(2)
13.8 Summary
236(1)
Problems
236(1)
Projects
236(1)
References
237(1)
14. Presenting Metrics Effectively to Management 238(14)
14.1 Decide on the Metrics
239(1)
14.2 Draw the Picture
240(3)
14.3 Create a Dashboard
243(1)
14.4 Drilling for Information
243(4)
14.5 Example for the Big Cheese
247(2)
14.6 Evolving Metrics
249(1)
14.7 Summary
250(1)
Problems
250(1)
Project
251(1)
Reference
251(1)
Index 252

An electronic version of this book is available through VitalSource.

This book is viewable on PC, Mac, iPhone, iPad, iPod Touch, and most smartphones.

By purchasing, you will be able to view this book online, as well as download it, for the chosen number of days.

Digital License

You are licensing a digital product for a set duration. Durations are set forth in the product description, with "Lifetime" typically meaning five (5) years of online access and permanent download to a supported device. All licenses are non-transferable.

More details can be found here.

A downloadable version of this book is available through the eCampus Reader or compatible Adobe readers.

Applications are available on iOS, Android, PC, Mac, and Windows Mobile platforms.

Please view the compatibility matrix prior to purchase.