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Software Architecture Metrics - Helion

Software Architecture Metrics
ebook
Autor: Christian Ciceri, Dave Farley, Neal Ford
ISBN: 9781098112189
stron: 218, Format: ebook
Data wydania: 2022-05-18
Ksi─Ögarnia: Helion

Cena ksi─ů┼╝ki: 203,15 z┼é (poprzednio: 236,22 z┼é)
Oszczędzasz: 14% (-33,07 zł)

Dodaj do koszyka Software Architecture Metrics

Software architecture metrics are key to the maintainability and architectural quality of a software project and they can warn you about dangerous accumulations of architectural and technical debt early in the process. In this practical book, leading hands-on software architects share case studies to introduce metrics that every software architect should know.

This isn't a book about theory. It's more about practice and implementation, about what has already been tried and worked. Detecting software architectural issues early is crucial for the success of your software: it helps mitigate the risk of poor performance and lowers the cost of repairing those issues. Written by practitioners for software architects and software developers eager to explore successful case studies, this guide will help you learn more about decision and measurement effectiveness.

Through contributions from 10 prominent practitioners, this book shares key software architecture metrics to help you set the right KPIs and measure the results. You'll learn how to:

  • Measure how well your software architecture is meeting your goals
  • Choose the right metrics to track (and skip the ones you don't need)
  • Improve observability, testability, and deployability
  • Prioritize software architecture projects
  • Build insightful and relevant dashboards

Dodaj do koszyka Software Architecture Metrics

 

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Dodaj do koszyka Software Architecture Metrics

Spis tre┼Ťci

Software Architecture Metrics eBook -- spis treÂci

  • Preface
    • What Will You Learn?
    • Who This Book Is For
    • Conventions Used in This Book
    • OReilly Online Learning
    • How to Contact Us
    • Acknowledgments
      • Christian Ciceri
      • Dave Farley
      • Neal Ford
      • Andrew Harmel-Law
      • Michael Keeling
      • Carola Lilienthal
      • Joo Rosa
      • Alexander von Zitzewitz
      • Rene Weiss
      • Eoin Woods
  • 1. Four Key Metrics Unleashed
    • Definition and Instrumentation
    • Refactoring Your Mental Model
      • Pipelines as Your First Port of Call
      • Locating Your Instrumentation Points
        • Commit timestamp
        • Deployment timestamp
        • Complexities arising from multistage and fan-in pipelines
        • Monitoring for service failures
    • Capture and Calculation
    • Display and Understanding
      • Target Audience
      • Visualization
        • Deployment frequency
        • Lead time for changes
        • Change failure rate
        • Time to restore service
      • Front Page
    • Discussions and Understanding
    • Ownership and Improvement
    • Conclusion
  • 2. The Fitness Function Testing Pyramid: An Analogy for Architectural Tests and Metrics
    • Fitness Functions and Metrics
      • Fitness Functions: Test Coverage
      • Fitness Functions: Integration Tests with Network Latency
    • Introduction to Fitness Function Categories
      • Mandatory Fitness Function Categories
        • Is the feedback atomic or holistic?
        • What triggers test execution?
        • Where is the test executed?
        • Metric type
        • Automated versus manual
        • Quality attribute requirements
      • Optional Fitness Function Categories
        • Is the fitness function temporary or permanent?
        • Is the fitness function static or dynamic?
        • Who is the target audience?
        • Where will your function and metric be applied?
      • Fitness Function Categories: Catalog Overview
    • The Testing Pyramid
    • The Fitness Function Testing Pyramid
      • The Top Layer
      • The Middle Layer
      • The Bottom Layer
    • Examples and Their Full Categorization
    • Fully Categorizing Top-Layer Examples
    • Developing Your Fitness Functions and Metrics
    • Conclusion
  • 3. Evolutionary Architecture: Guiding Architecture with Testability and Deployability
    • The Importance of Learning and Discovery
    • The Tools of Sustainable Change
    • Testability: Creating High-Quality Systems
    • Deployability: Scaling Development of Our Systems
    • Conclusion
  • 4. Improve Your Architecture with the Modularity Maturity Index
    • Technical Debt
    • Origination of Technical Debt
    • Assessment with the MMI
    • Modularity
    • Hierarchy
    • Pattern Consistency
    • Calculating the MMI
    • Architecture Review to Determine the MMI
    • Conclusion
  • 5. Private Builds and Metrics: Tools for Surviving DevOps Transitions
    • Key Terms
      • CI/CD
      • DevOps
    • The Ownership Shift
    • Empowering the Local Environment Again
    • The Private Build
    • Case Study: The Unstable Trunk
      • Bug A1
      • Bug A2
      • Bug A3
      • Bug A4
    • Case Study: The Blocked Consultant
    • Metrics
      • Time to Feedback
      • Evitable Integration Issues in the Deployed Application per Iteration
      • Time Spent Restoring Trunk Stability per Iteration
      • The Cost of Private Builds
    • Metrics in Practice
      • High Time to Feedback, High Evitable Integration Issues, Low Time to Trunk Stability
      • Low Time to Feedback, High Evitable Integration Issues, Low Time to Trunk Stability
      • High Time to Feedback, Low Evitable Integration Issues, Low Time to Trunk Stability
      • Low Evitable Integration Issues and High Time to Trunk Stability
    • Conclusion
  • 6. Scaling an Organization: The Central Role of Software Architecture
    • YourFinFreedom Breaks the Monolith
    • Implementing a Distributed Big Ball of Mud
    • Seeking Direction
    • From Best Effort to Intentional Effort
    • Increasing Software Architecture Intentionality, Guided by Metrics
    • Managing Expectations with Communication
    • Learning and Evolving the Architecture
    • And What About Anna?
    • Conclusion
  • 7. The Role of Measurement in Software Architecture
    • Adding Measurement to Software Architecture
    • Measurement Approaches
      • Runtime Measurement of Applications and Infrastructure
      • Software Analysis
      • Design Analysis
      • Estimates and Models
      • Fitness Functions
    • Measuring System Qualities
      • Performance
        • Considerations when measuring performance
        • Common problems when measuring performance
      • Scalability
        • Considerations when measuring scalability
        • Common problems when measuring scalability
      • Availability
        • Considerations when measuring availability
        • Common problems when measuring availability
      • Security
        • Considerations when measuring security
        • Common problems when measuring security
    • Getting Started
    • Hypothetical Case Study
    • Pitfalls
    • Conclusion
  • 8. Progressing from Metrics to Engineering
    • The Path to Fitness Functions
    • From Metrics to Engineering
    • Automation Operationalizes Metrics
    • Case Study: Coupling
    • Case Study: Zero-Day Security Check
    • Case Study: Fidelity Fitness Functions
    • Conclusion
  • 9. Using Software Metrics to Ensure Maintainability
    • The Case for Using Metrics
      • Entropy Kills Software
      • The Toxicity of Cyclic Dependencies
      • How Metrics Can Help
    • Why Are Metrics Not More Widely Used?
    • Tools to Gather Metrics
    • Useful Metrics
      • Metrics to Measure Coupling and Structural Erosion
        • Average component dependency, propagation cost, and related metrics
        • Cyclicity and relative cyclicity
        • Structural debt index
        • Maintainability level
      • Metrics to Measure Size and Complexity
        • Size metrics
        • Cyclomatic complexity
        • Indentation debt
      • Change History Metrics
        • Change frequency
        • Code churn
        • Number of authors
        • Using version-control metrics to find good candidates for refactoring
      • Other Useful Metrics
        • Component rank
        • LCOM4
    • Architectural Fitness Functions
    • How to Track Metrics over Time
    • A Few Golden Rules for Better Software
    • Conclusion
  • 10. Measure the Unknown with the Goal-Question-Metric Approach
    • The Goal-Question-Metric Approach
      • Create a GQM Tree
      • Prioritize Metrics and Devise a Data Collection Strategy
    • Case Study: The Team That Learned to See the Future
      • System Context
      • Incident #1: Too Many Requests to the Foo Service
        • What does failure look like?
        • Operational visibility and architectural improvements
      • Incident #2: Seeing the Future
      • Reflection
    • Run a GQM Workshop
      • Workshop Summary
        • Benefits
        • Participants
        • Preparation and materials
        • Outcomes
      • Workshop Steps
      • Facilitation Guidelines and Hints
        • Example
    • Conclusion
  • Index

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