Performance Solutions
A Practical Guide to Creating Responsive, Scalable Software
Published on 2. October 2001
Book
Hardback
544 pages
978-0-201-72229-1 (ISBN)
Description
Software development is replete with risks. Will the finished software run quickly enough? Will the underlying hardware and network infrastructure be sufficient? Will the system scale? You can now get the answers you need, up-front, in time to act. This book introduces Software Performance Engineering (SPE), a proven step-by-step methodology for predicting the development challenges and performance of any object-oriented system -- and for managing development to achieve performance objectives. Performance experts Connie Smith and Lloyd Williams show how to build quantitative models of software before it is built, analyzing performance based on proposed architecture and design. Learn how to elicit performance objectives, gather relevant data, and evaluate performance throughout development and the rest of the software lifecycle. For software engineers, developers, architects, analysts, performance specialists, project managers, and other IT professionals who want to deliver higher-performance object-oriented software systems.
More details
Language
English
Place of publication
Boston
United States
Publishing group
Pearson Education (US)
Target group
College/higher education
Dimensions
Height: 193 mm
Width: 241 mm
Thickness: 33 mm
Weight
875 gr
ISBN-13
978-0-201-72229-1 (9780201722291)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
Connie U. Smith, Ph.D., is a principal consultant of the Performance Engineering Services Division of L&S Computer Technology, Inc. She is internationally recognized for her work in defining the field of software performance engineering and integrating SPE into the development of new software systems. She is the author of Performance Engineering of Software Systems (Addison-Wesley, 1990) and received the Computer Measurement Group's AA Michelson Award for technical excellence and professional contributions for her SPE work.
Lloyd G. Williams, Ph.D., is a principal consultant at Software Engineering Research, where he specializes in the development and evaluation of software architectures to meet quality objectives, including performance, reliability, modifiability, and reusability. His experience includes work on systems in fields such as process control, avionics, telecommunications, electronic funds transfer, Web-based systems, software development tools and environments, and medical instrumentation. He has presented professional development seminars and consulted on software development for more than 100 organizations worldwide.
0201722291AB07162001
Lloyd G. Williams, Ph.D., is a principal consultant at Software Engineering Research, where he specializes in the development and evaluation of software architectures to meet quality objectives, including performance, reliability, modifiability, and reusability. His experience includes work on systems in fields such as process control, avionics, telecommunications, electronic funds transfer, Web-based systems, software development tools and environments, and medical instrumentation. He has presented professional development seminars and consulted on software development for more than 100 organizations worldwide.
0201722291AB07162001
Content
Foreword by Grady Booch.
Foreword by Paul Clements.
Preface.
I. INTRODUCTION AND OVERVIEW.
1. Introduction.
Software and Performance.
Responsiveness.
Scalability.
The Importance of Performance.
Consequences of Performance Failures.
Causes of Performance Failures.
Getting It Right.
How Should You Manage Performance?
Reactive Performance Management.
Proactive Performance Management.
Software Performance Engineering.
SPE Modeling Strategies.
SPE Models.
SPE for Object-Oriented Systems.
What Does It Cost?
What Do You Need?
Summary.
2: SPE Quick View.
SPE Process for Object-Oriented Systems.
Case Study.
Assess Performance Risk (Step 1).
Identify Critical Use Cases (Step 2).
Select Key Performance Scenarios (Step 3).
Establish Performance Objectives (Step 4).
Construct Performance Models (Step 5).
Determine Software Resource Requirements (Step 6).
Add Computer Resource Requirements (Step 7).
Evaluate the Models (Step 8).
Verify and Validate the Models (Step 9).
SPE in the Unified Software Process.
Performance Solutions.
Performance Principles.
Performance Patterns.
Performance Antipatterns.
Implementation Solutions.
Summary.
3: SPE and the UML.
Overview.
Extending the UML.
Stereotypes.
Tagged Values.
Constraints.
Use Cases and Scenarios.
Use Cases.
Scenarios.
Extensions to Sequence Diagram Notation.
Instance Decomposition.
Looping, Alternation, and References.
Specifying Time.
Timing Marks.
Time Expressions.
Timing Constraints.
Time in Sequence Diagrams.
Concurrency.
Threads and Processes.
Coregions.
Parallel Composition.
Synchronization.
Summary.
II. SPE MODELS.
4: Software Execution Models.
Purpose.
Representing Software Execution Models.
Execution Graphs.
Execution Graph Restrictions.
Model Solutions.
Basic Solution Algorithms.
More Advanced Solution Techniques.
Analysis Procedures.
Execution Graphs from Sequence Diagrams.
ICAD Case Study.
Architecture 1.
Architecture 2.
Analysis of Results.
Architecture 3.
Modeling Hints.
Summary.
5: Web Applications and Other Distributed Systems.
Introduction.
Web Applications.
Distributed Object Technology.
Middleware.
Limitations of Distributed Object Technology.
Effective Development with Distributed Object Technology.
Modeling Distributed System Interactions.
Types of System Interactions.
Software Execution Model Representation.
Representing Middleware Overhead.
Software Model Solution Approximations.
Example: Web e-Commerce Application.
Database Scenario.
Order Process Scenario.
Example Summary.
Modeling Hints.
Summary.
6: System Execution Models.
Introduction.
System Model Basics.
Performance Metrics.
Solving the Queueing Model.
Networks of Queues.
Deriving System Model Parameters from Software Model Results.
Using the System Model for SPE.
Advanced System Models.
Alternate Solution Methods.
Schedulability.
Distributed System Case Study.
Synchronization Model.
Modeling Hints.
Summary.
III. DATA COLLECTION.
7: SPE Data Collection.
Introduction.
SPE Data Requirements.
Key Performance Scenarios.
Performance Objectives.
Execution Environment.
Software Resource Requirements.
Computer Resource Requirements.
Data Gathering Issues.
Performance Walkthrough.
Topics.
When to Conduct Performance Walkthroughs.
Example.
Tips for a Successful Performance Walkthrough.
Resource Estimation Techniques.
Use Measurements.
Study Measurements.
Use a Mentor.
Best-Worst Case Estimates.
What to Estimate.
Estimating I/O Requirements.
Estimating Network Messages
Obtaining Computer Resource Requirements.
Summary.
8: Software Measurement and Instrumentation.
Introduction.
What Should You Measure?
Workload Data and Data Characteristics.
Path Characteristics.
Software Resources and Processing Overhead.
Computer Resource Usage.
Planning for Performance Measurement.
Key Considerations.
Performance Benchmarks.
Designing and Conducting Measurement Studies.
Performance Measurement Concepts.
Terminology.
Factors That May Affect Measurements.
Data Collection Techniques and Tools.
Data Collection Techniques.
Measuring SPE Data.
Instrumentation.
Instrumentation Design Considerations.
Implementation Alternatives.
Data Reporting.
Application Resource Measurement.
Summary.
IV. PERFORMANCE SOLUTIONS.
9: Performance-Oriented Design.
Principles for Performance-Oriented Design.
Performance Control Principles.
Performance Objectives Principle.
Instrumenting Principle.
Independent Principles.
Centering Principle.
Fixing-Point Principle.
Locality Principle.
Processing Versus Frequency Principle.
Synergistic Principles.
Shared Resources Principle.
Parallel Processing Principle.
Spread-the-Load Principle.
Using the Principles.
Summary.
10: Performance Patterns.
Overview.
Fast Path.
Problem.
Solution.
Benefits.
Consequences.
First Things First.
Problem.
Solution.
Benefits.
Consequences.
Coupling.
Problem.
Solution.
Benefits.
Consequences.
Batching.
Problem.
Solution.
Benefits.
Consequences.
Alternate Routes.
Problem.
Solution.
Benefits.
Consequences.
Flex Time.
Problem.
Solution.
Benefits.
Consequences.
Slender Cyclic Functions.
Problem.
Solution.
Benefits.
Consequences.
Summary.
11: Performance Antipatterns.
Overview.
The "god" Class.
Problem.
Solution.
Excessive Dynamic Allocation.
Problem.
Solution.
Circuitous Treasure Hunt.
Problem.
Solution.
The One-Lane Bridge.
Problem.
Solution.
Traffic Jam.
Problem.
Solution.
Summary.
12: Implementation Solutions.
Overview.
Performance Tuning.
General Performance Solutions.
Fast Path Speed-Up.
Improving Scalability.
Algorithm and Data Structure Choices.
Time Versus Space Trade-Offs.
Hardware/Software Platform Dependencies.
Performance Solutions for Object-Oriented Software.
Language-Independent Solutions.
C++ Solutions.
Java Solutions.
Summary.
V. APPLICATIONS.
13: Web Applications.
Introduction.
Performance Issues.
SPE Models for Web Applications.
Case Study: Nachtfliegen.com.
Plan Itinerary Scenario.
Software Model.
Hardware/Software Environment.
Resource Requirements.
Software Model Solution.
Performance Improvements.
System Execution Model.
Sensitivity and Scalability Analysis.
Typical Performance Problems.
Summary.
14: Embedded Real-Time Systems.
Introduction.
Embedded Real-Time Systems Background.
Timing Requirements.
Hardware Constraints.
Real-Time Operating Systems.
Distributed Systems.
Database.
Performance Issues.
Response Time and Throughput.
Schedulability.
SPE Models for Embedded Real-Time Systems.
Case Study: Telephony Switching.
Overview.
Architecture and Design.
Typical Performance Problems.
Summary.
VI. MAKING SPE HAPPEN.
15: The SPE Process.
Introduction.
The SPE Process.
Assess Performance Risk.
Identify Critical Use Cases.
Select Key Performance Scenarios.
Establish Performance Objectives.
Construct Performance Models.
Determine Software Resource Requirements.
Add Computer Resource Requirements.
Evaluate the Models.
Verify and Validate Models.
Late Life Cycle SPE Activities.
More Detailed Models.
More Precise Data.
Performance Testing.
Baseline Models.
Post-Deployment Performance Management.
Evolutionary Changes.
Capacity Management.
SPE Artifacts.
Performance Management Plans.
Performance V&V Plan.
SPE Configuration Management Plan.
Performance Drivers.
Performance Scenarios.
Performance Objectives.
Execution Environment Specifications.
Performance Models.
Model Results.
Performance Instrumentation.
Performance V&V Reports.
Performance Test Plans.
Performance Test Results.
Integrating SPE Into Your Software Process.
The Waterfall Model.
The Spiral Model.
SPE in the Unified Process.
Summary.
16: Implementing SPE.
Introduction.
Tools.
Modeling Tools.
Development Tools.
SPE Adoption and Use.
Experience.
Key Considerations.
Pilot Projects.
Critical Success Factors for Adoption and Use.
SPE Implementation Strategies.
Organizational Issues.
Who Pays for SPE?
Costs.
Risks.
Critical Factors for Successful Projects.
SPE Future.
Summary.
VII. APPENDIXES.
Appendix A: UML Notation.
Use Case Diagrams.
Sequence Diagrams.
Basic Sequence Diagrams.
Augmented Sequence Diagrams.
Deployment Diagrams.
Stereotypes, Tagged Values, and Constraints.
Stereotypes.
Tagged Values.
Constraints.
Appendix B: SPE Modeling Notations.
Execution Graph Notation.
Basic Nodes.
Synchronization Nodes.
Information Processing Graph Notation.
Bibliography.
Index. 0201722291T09102001
Foreword by Paul Clements.
Preface.
I. INTRODUCTION AND OVERVIEW.
1. Introduction.
Software and Performance.
Responsiveness.
Scalability.
The Importance of Performance.
Consequences of Performance Failures.
Causes of Performance Failures.
Getting It Right.
How Should You Manage Performance?
Reactive Performance Management.
Proactive Performance Management.
Software Performance Engineering.
SPE Modeling Strategies.
SPE Models.
SPE for Object-Oriented Systems.
What Does It Cost?
What Do You Need?
Summary.
2: SPE Quick View.
SPE Process for Object-Oriented Systems.
Case Study.
Assess Performance Risk (Step 1).
Identify Critical Use Cases (Step 2).
Select Key Performance Scenarios (Step 3).
Establish Performance Objectives (Step 4).
Construct Performance Models (Step 5).
Determine Software Resource Requirements (Step 6).
Add Computer Resource Requirements (Step 7).
Evaluate the Models (Step 8).
Verify and Validate the Models (Step 9).
SPE in the Unified Software Process.
Performance Solutions.
Performance Principles.
Performance Patterns.
Performance Antipatterns.
Implementation Solutions.
Summary.
3: SPE and the UML.
Overview.
Extending the UML.
Stereotypes.
Tagged Values.
Constraints.
Use Cases and Scenarios.
Use Cases.
Scenarios.
Extensions to Sequence Diagram Notation.
Instance Decomposition.
Looping, Alternation, and References.
Specifying Time.
Timing Marks.
Time Expressions.
Timing Constraints.
Time in Sequence Diagrams.
Concurrency.
Threads and Processes.
Coregions.
Parallel Composition.
Synchronization.
Summary.
II. SPE MODELS.
4: Software Execution Models.
Purpose.
Representing Software Execution Models.
Execution Graphs.
Execution Graph Restrictions.
Model Solutions.
Basic Solution Algorithms.
More Advanced Solution Techniques.
Analysis Procedures.
Execution Graphs from Sequence Diagrams.
ICAD Case Study.
Architecture 1.
Architecture 2.
Analysis of Results.
Architecture 3.
Modeling Hints.
Summary.
5: Web Applications and Other Distributed Systems.
Introduction.
Web Applications.
Distributed Object Technology.
Middleware.
Limitations of Distributed Object Technology.
Effective Development with Distributed Object Technology.
Modeling Distributed System Interactions.
Types of System Interactions.
Software Execution Model Representation.
Representing Middleware Overhead.
Software Model Solution Approximations.
Example: Web e-Commerce Application.
Database Scenario.
Order Process Scenario.
Example Summary.
Modeling Hints.
Summary.
6: System Execution Models.
Introduction.
System Model Basics.
Performance Metrics.
Solving the Queueing Model.
Networks of Queues.
Deriving System Model Parameters from Software Model Results.
Using the System Model for SPE.
Advanced System Models.
Alternate Solution Methods.
Schedulability.
Distributed System Case Study.
Synchronization Model.
Modeling Hints.
Summary.
III. DATA COLLECTION.
7: SPE Data Collection.
Introduction.
SPE Data Requirements.
Key Performance Scenarios.
Performance Objectives.
Execution Environment.
Software Resource Requirements.
Computer Resource Requirements.
Data Gathering Issues.
Performance Walkthrough.
Topics.
When to Conduct Performance Walkthroughs.
Example.
Tips for a Successful Performance Walkthrough.
Resource Estimation Techniques.
Use Measurements.
Study Measurements.
Use a Mentor.
Best-Worst Case Estimates.
What to Estimate.
Estimating I/O Requirements.
Estimating Network Messages
Obtaining Computer Resource Requirements.
Summary.
8: Software Measurement and Instrumentation.
Introduction.
What Should You Measure?
Workload Data and Data Characteristics.
Path Characteristics.
Software Resources and Processing Overhead.
Computer Resource Usage.
Planning for Performance Measurement.
Key Considerations.
Performance Benchmarks.
Designing and Conducting Measurement Studies.
Performance Measurement Concepts.
Terminology.
Factors That May Affect Measurements.
Data Collection Techniques and Tools.
Data Collection Techniques.
Measuring SPE Data.
Instrumentation.
Instrumentation Design Considerations.
Implementation Alternatives.
Data Reporting.
Application Resource Measurement.
Summary.
IV. PERFORMANCE SOLUTIONS.
9: Performance-Oriented Design.
Principles for Performance-Oriented Design.
Performance Control Principles.
Performance Objectives Principle.
Instrumenting Principle.
Independent Principles.
Centering Principle.
Fixing-Point Principle.
Locality Principle.
Processing Versus Frequency Principle.
Synergistic Principles.
Shared Resources Principle.
Parallel Processing Principle.
Spread-the-Load Principle.
Using the Principles.
Summary.
10: Performance Patterns.
Overview.
Fast Path.
Problem.
Solution.
Benefits.
Consequences.
First Things First.
Problem.
Solution.
Benefits.
Consequences.
Coupling.
Problem.
Solution.
Benefits.
Consequences.
Batching.
Problem.
Solution.
Benefits.
Consequences.
Alternate Routes.
Problem.
Solution.
Benefits.
Consequences.
Flex Time.
Problem.
Solution.
Benefits.
Consequences.
Slender Cyclic Functions.
Problem.
Solution.
Benefits.
Consequences.
Summary.
11: Performance Antipatterns.
Overview.
The "god" Class.
Problem.
Solution.
Excessive Dynamic Allocation.
Problem.
Solution.
Circuitous Treasure Hunt.
Problem.
Solution.
The One-Lane Bridge.
Problem.
Solution.
Traffic Jam.
Problem.
Solution.
Summary.
12: Implementation Solutions.
Overview.
Performance Tuning.
General Performance Solutions.
Fast Path Speed-Up.
Improving Scalability.
Algorithm and Data Structure Choices.
Time Versus Space Trade-Offs.
Hardware/Software Platform Dependencies.
Performance Solutions for Object-Oriented Software.
Language-Independent Solutions.
C++ Solutions.
Java Solutions.
Summary.
V. APPLICATIONS.
13: Web Applications.
Introduction.
Performance Issues.
SPE Models for Web Applications.
Case Study: Nachtfliegen.com.
Plan Itinerary Scenario.
Software Model.
Hardware/Software Environment.
Resource Requirements.
Software Model Solution.
Performance Improvements.
System Execution Model.
Sensitivity and Scalability Analysis.
Typical Performance Problems.
Summary.
14: Embedded Real-Time Systems.
Introduction.
Embedded Real-Time Systems Background.
Timing Requirements.
Hardware Constraints.
Real-Time Operating Systems.
Distributed Systems.
Database.
Performance Issues.
Response Time and Throughput.
Schedulability.
SPE Models for Embedded Real-Time Systems.
Case Study: Telephony Switching.
Overview.
Architecture and Design.
Typical Performance Problems.
Summary.
VI. MAKING SPE HAPPEN.
15: The SPE Process.
Introduction.
The SPE Process.
Assess Performance Risk.
Identify Critical Use Cases.
Select Key Performance Scenarios.
Establish Performance Objectives.
Construct Performance Models.
Determine Software Resource Requirements.
Add Computer Resource Requirements.
Evaluate the Models.
Verify and Validate Models.
Late Life Cycle SPE Activities.
More Detailed Models.
More Precise Data.
Performance Testing.
Baseline Models.
Post-Deployment Performance Management.
Evolutionary Changes.
Capacity Management.
SPE Artifacts.
Performance Management Plans.
Performance V&V Plan.
SPE Configuration Management Plan.
Performance Drivers.
Performance Scenarios.
Performance Objectives.
Execution Environment Specifications.
Performance Models.
Model Results.
Performance Instrumentation.
Performance V&V Reports.
Performance Test Plans.
Performance Test Results.
Integrating SPE Into Your Software Process.
The Waterfall Model.
The Spiral Model.
SPE in the Unified Process.
Summary.
16: Implementing SPE.
Introduction.
Tools.
Modeling Tools.
Development Tools.
SPE Adoption and Use.
Experience.
Key Considerations.
Pilot Projects.
Critical Success Factors for Adoption and Use.
SPE Implementation Strategies.
Organizational Issues.
Who Pays for SPE?
Costs.
Risks.
Critical Factors for Successful Projects.
SPE Future.
Summary.
VII. APPENDIXES.
Appendix A: UML Notation.
Use Case Diagrams.
Sequence Diagrams.
Basic Sequence Diagrams.
Augmented Sequence Diagrams.
Deployment Diagrams.
Stereotypes, Tagged Values, and Constraints.
Stereotypes.
Tagged Values.
Constraints.
Appendix B: SPE Modeling Notations.
Execution Graph Notation.
Basic Nodes.
Synchronization Nodes.
Information Processing Graph Notation.
Bibliography.
Index. 0201722291T09102001