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Mastering Apex Programming

You're reading from   Mastering Apex Programming A developer's guide to learning advanced techniques and best practices for building robust Salesforce applications

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Product type Paperback
Published in Nov 2020
Publisher Packt
ISBN-13 9781800200920
Length 368 pages
Edition 1st Edition
Languages
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Author (1):
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Paul Battisson Paul Battisson
Author Profile Icon Paul Battisson
Paul Battisson
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Toc

Table of Contents (21) Chapters Close

Preface 1. Section 1 – Triggers, Testing, and Security
2. Chapter 1: Common Apex Mistakes FREE CHAPTER 3. Chapter 2: Debugging Apex 4. Chapter 3: Triggers and Managing Trigger Execution 5. Chapter 4: Exceptions and Exception Handling 6. Chapter 5: Testing Apex Code 7. Chapter 6: Secure Apex Programming 8. Section 2 – Asynchronous Apex and Apex REST
9. Chapter 7: Utilizing Future Methods 10. Chapter 8: Working with Batch Apex 11. Chapter 9: Working with Queueable Apex 12. Chapter 10: Scheduling Apex Jobs 13. Chapter 11: Using Platform Events 14. Chapter 12: Apex REST and Custom Web Services 15. Section 3 – Apex Performance
16. Chapter 13: Performance and the Salesforce Governor Limits 17. Chapter 14: Performance Profiling 18. Chapter 15: Improving Apex Performance 19. Chapter 16: Performance and Application Architectures 20. Other Books You May Enjoy

Summary

In this chapter, we have dealt with the importance of testing our Apex code and how we can improve the quality and integrity of our tests. Testing is a key part of the software development life cycle, and writing clear and well-structured tests that validate assumptions and outcomes through assertions is extremely important in providing confidence in your system.

We also saw how we can improve the creation of test data for our tests in a number of ways. The largest performance problem for Apex tests is the repeated creation of data in different unit tests, as the system must run through the save order of execution multiple times, taking up time and governor resources. By separating our test data into a factory, we can ensure that data is created in a consistent manner and save ourselves additional rework should the code need updating to accommodate new required fields and processing. Calling our test data creation from a method annotated by @TestSetup ensures that the data...

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