An effective, quantitative approach for estimating and managing
software projects
How many people do I need? When will the quality be good enough for
commercial sale? Can this really be done in two weeks? Rather than
relying on instinct, the authors of Software Measurement and
Estimation offer a new, tested approach that includes the
quantitative tools, data, and knowledge needed to make sound
estimations.
The text begins with the foundations of measurement, identifies the
appropriate metrics, and then focuses on techniques and tools for
estimating the effort needed to reach a given level of quality and
performance for a software project. All the factors that impact
estimations are thoroughly examined, giving you the tools needed to
regularly adjust and improve your estimations to complete a project
on time, within budget, and at an expected level of quality.
This text includes several features that have proven to be
successful in making the material accessible and easy to
master:
* Simple, straightforward style and logical presentation and
organization enables you to build a solid foundation of theory and
techniques to tackle complex estimations
* Examples, provided throughout the text, illustrate how to use
theory to solve real-world problems
* Projects, included in each chapter, enable you to apply your
newfound knowledge and skills
* Techniques for effective communication of quantitative data help
you convey your findings and recommendations to peers and
management
Software Measurement and Estimation: A Practical Approach allows
practicing software engineers and managers to better estimate,
manage, and effectively communicate the plans and progress of their
software projects. With its classroom-tested features, this is an
excellent textbook for advanced undergraduate-level and graduate
students in computer science and software engineering.
An Instructor Support FTP site is available from the Wiley
editorial department.
Autorentext
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.
Klappentext
An effective, quantitative approach for estimating and managing software projects
How many people do I need? When will the quality be good enough for commercial sale? Can this really be done in two weeks? Rather than relying on instinct, the authors of Software Measurement and Estimation offer a new, tested approach that includes the quantitative tools, data, and knowledge needed to make sound estimations.
The text begins with the foundations of measurement, identifies the appropriate metrics, and then focuses on techniques and tools for estimating the effort needed to reach a given level of quality and performance for a software project. All the factors that impact estimations are thoroughly examined, giving you the tools needed to regularly adjust and improve your estimations to complete a project on time, within budget, and at an expected level of quality.
This text includes several features that have proven to be successful in making the material accessible and easy to master:
- Simple, straightforward style and logical presentation and organization enables you to build a solid foundation of theory and techniques to tackle complex estimations
- Examples, provided throughout the text, illustrate how to use theory to solve real-world problems
- Projects, included in each chapter, enable you to apply your newfound knowledge and skills
- Techniques for effective communication of quantitative data help you convey your findings and recommendations to peers and management
Software Measurement and Estimation: A Practical Approach allows practicing software engineers and managers to better estimate, manage, and effectively communicate the plans and progress of their software projects. With its classroom-tested features, this is an excellent textbook for advanced undergraduate-level and graduate students in computer science and software engineering.
Inhalt
Acknowledgments.
1. Introduction.
1.1 Objective.
1.2 Approach.
1.3 Motivation.
1.4 Summary.
References.
Chapter 1 Side Bar.
2. What to Measure.
2.1 Method 1: The Goal Question Metrics Approach.
2.2 Extension to GQM: Metrics Mechanism is Important.
2.3 Method 2: Decision Maker Model.
2.4 Method 3: Standards Driven Metrics.
2.5 What to Measure is a Function of Time.
2.6 Summary.
References.
Exercises.
Project.
3. Fundamentals of Measurement.
3.1 Initial Measurement Exercise.
3.2 The Challenge of Measurement.
3.3 Measurement Models.
3.3.1 Text Models.
3.3.2 Diagrammatic Models.
3.3.3 Algorithmic Models.
3.3.4 Model Examples: Response Time.
3.3.5 The Pantometric Paradigm - How to Measure Anything.
3.4 Meta-Model for Metrics.
3.5 The Power of Measurement.
3.6 Measurement Theory.
3.6.1 Introduction to Measurement Theory.
3.6.2 Measurement Scales.
3.6.3 Measures of Central Tendency and Variability.
3.6.3.1 Measures of Central Tendency.
3.6.3.2 Measures of Variability.
3.6.4 Validity and Reliability of Measurement.
3.6.5 Measurement Error.
3.7 Accuracy versus Precision and the Limits of Software Measurement.
3.7.1 Summary.
3.7.2 Problems.
3.7.3 Project.
References.
4. Measuring the Size of Software.
4.1 Physical Measurements of Software.
4.1.1 Measuring Lines of Code.
4.1.1.1 Code Counting Checklists.
4.1.2 Language Productivity Factor.
4.1.3 Counting Reused and Refactored Code.
4.1.4 Counting Non-Procedural Code Length.
4.1.5 Measuring the Length of Specifications and Design.
4.2 Measuring Functionality.
4.2.1 Function Points.
4.2.1.1 Counting Function Points.
4.2.2 Function Point Counting Exercise.
4.2.3 Converting Function Points to Physical Size.
4.2.4 Converting Function Points to Effort.
4.2.5 Other Function Point Engineering Rules.
4.2.6 Function Point Pros and Cons.
4.3 Feature Points.
4.4 Size Summary.
4.5 Size Exercises.
4.6 Theater Tickets Project.
References.
5. Measuring Complexity.
5.1 Structural Complexity.
5.1.1 Size as a Complexity Measure.
5.1.1.1 System Size and Complexity.
5.1.1.2 Module Size and Complexity.
5.1.2 Cyclomatic Complexity.
5.1.3 Halstead's Metrics.
5.1.4 Information Flow Metrics.
5.1.5 System Complexity.
5.1.5.1 Maintainability Index.
5.1.5.2 The Agresti-Card System Complexity Metric.
5.1.6 Object-Oriented Design Metrics.
5.1.7 Structural Complexity Summary.
5.2 Conceptual Complexity.
5.3 Computational Complexity.
5.4 Complexity Metrics Summary.
5.5 Complexity Exercises.
5.6 Projects.
References.
6. Estimating Effort.
6.1 Effort Estimation …