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Testable JavaScript

Cover of Testable JavaScript by Mark Ethan Trostler Published by O'Reilly Media, Inc.
  1. Testable JavaScript
  2. Dedication
  3. Preface
    1. The Goal of This Book
    2. Who This Book Is For
    3. Who This Book Is Not For
    4. Who I Am
    5. What You Will Learn from This Book
      1. Content
    6. If You Like (or Don’t Like) This Book
    7. Recap
    8. How to Contact Us
    9. Conventions Used in This Book
    10. Using Code Examples
    11. Safari® Books Online
    12. Thanks!
  4. 1. Testable JavaScript
    1. Prior Art
      1. Agile Development
      2. Test-Driven Development
      3. Behavior-Driven Development
      4. The Best Approach?
    2. Code Is for People
      1. Why
      2. What
      3. How
    3. Beyond Application Code
      1. Testing
      2. Debugging
    4. Recap
  5. 2. Complexity
    1. Code Size
    2. JSLint
    3. Cyclomatic Complexity
    4. Reuse
    5. Fan-Out
    6. Fan-In
    7. Coupling
      1. Content Coupling
      2. Common Coupling
      3. Control Coupling
      4. Stamp Coupling
      5. Data Coupling
      6. No Coupling
      7. Instantiation
    8. Coupling Metrics
    9. Coupling in the Real World
      1. Testing Coupled Code
    10. Dependency Injection
    11. Comments
      1. YUIDoc
      2. JSDoc
      3. Docco/Rocco
    12. The Human Test
    13. Recap
  6. 3. Event-Based Architectures
    1. The Benefits of Event-Based Programming
    2. The Event Hub
      1. Using the Event Hub
      2. Responses to Thrown Events
      3. Event-Based Architectures and MVC Approaches
      4. Event-Based Architectures and Object-Oriented Programming
      5. Event-Based Architectures and Software as a Service
    3. Web-Based Applications
    4. Testing Event-Based Architectures
    5. Caveats to Event-Based Architectures
      1. Scalability
      2. Broadcasting
      3. Runtime Checking
      4. Security
      5. State
    6. A Smarter Hub: The Event Switch
      1. Deployment
      2. An Implementation
      3. Sessions
      4. Extensibility
    7. Recap
  7. 4. Unit Tests
    1. A Framework
    2. Let’s Get Clean
    3. Writing Good Tests
      1. Isolation
      2. Scope
      3. Defining Your Functions
      4. Positive Testing
      5. Negative Testing
      6. Code Coverage
    4. Real-World Testing
      1. Dependencies
      2. Asynchronous Testing
    5. Running Tests: Client-Side JavaScript
      1. PhantomJS
      2. Selenium
    6. Running Tests: Server-Side JavaScript
      1. Jasmine
    7. Recap
  8. 5. Code Coverage
    1. Coverage Basics
    2. Code Coverage Data
    3. A Hands-on Example
      1. Instrumenting Files
      2. Anatomy of a Coveraged File
    4. Exercise/Deploy
      1. Client-Side JavaScript
      2. Server-Side JavaScript
    5. Persisting Coverage Information
      1. Unit Tests
      2. Integration Tests
    6. Generating Output
    7. Aggregation
    8. Hidden Files
    9. Coverage Goals
    10. Recap
  9. 6. Integration, Performance, and Load Testing
    1. Integration Testing
      1. Selenium
      2. CasperJS
    2. Performance Testing
      1. Generating HAR Files
      2. Viewing HAR Files
      3. Browser Performance Testing
    3. Load Testing
      1. Browser Load Testing
    4. Tracking Resource Usage
      1. Client-Side Tracking
      2. Server-Side Tracking
    5. Recap
  10. 7. Debugging
    1. In-Browser Debugging
      1. Firefox
      2. Chrome
      3. Safari
      4. Internet Explorer
    2. Node.js Debugging
    3. Remote Debugging
      1. Chrome
      2. PhantomJS
      3. Firefox
    4. Mobile Debugging
      1. Android 4
      2. iOS 6
      3. Adobe Edge Inspect
      4. Other Mobile Debugging Options
    5. Production Debugging
      1. Minified Code
      2. Source Maps
    6. Recap
  11. 8. Automation
    1. What to Automate
    2. When to Automate
    3. How to Automate
      1. Automating with Continuous Integration
      2. Automating the Development Environment
      3. Automating the Build Environment
      4. Deployment
    4. Recap
  12. Index
  13. About the Author
  14. Colophon
  15. Copyright
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Chapter 5. Code Coverage

Even though code coverage metrics can be misleading, they are still vital. While code coverage is typically associated with unit tests, it is equally easy to generate code coverage metrics from integration tests. And it is trivial to combine multiple code coverage reports into a single report that includes all your unit and integration tests, thereby providing a complete picture of exactly what code is covered by your full suite of tests.

Regardless of the coverage tools you utilize, the flow is similar: instrument JavaScript files for code coverage information, deploy or exercise those files, pull the coverage results and persist them into a local file, potentially combine coverage results from different tests, and either generate pretty HTML output or just get the coverage numbers and percentages you are interested in for upstream tools and reporting.

Coverage Basics

Code coverage measures if, and if so, how many times, a line of code is executed. This is useful for measuring the efficacy of your test code. In theory, the more lines that are “covered”, the more complete your tests are. However, the link between code coverage and test completeness can be tenuous.

Here is a simple Node.js function that returns the current stock price of a given symbol:

/** * Return current stock price for given symbol * in the callback * * @method getPrice * @param symbol <String> the ticker symbol * @param cb <Function> callback with results cb(error, value) * @param httpObj ...

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