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Salesforce Testing
Language
Articles
10/4/2024
10 minutes
6 testing metrics that’ll speed up your Salesforce release velocity (and how to track them)
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In Salesforce development, balancing speed and quality is an ongoing challenge.
As release deadlines loom, teams often face a difficult choice: cut corners on testing or push back the release date. Neither option’s ideal, but there's a better way forward that isn’t either-or.
By tracking the right testing metrics, you identify and address issues before they become bottlenecks.
For Salesforce leaders aiming to optimize their release cycles, here are six essential metrics you should be monitoring to minimize roadblocks and speed up Salesforce development velocity…
Defect Density measures the number of defects per unit of custom code or configuration. In Salesforce terms, this could be defects per Apex class, Lightning component, or Flow.
Why it matters: This metric is a key indicator of code quality. A lower defect density suggests higher-quality code, which typically leads to fewer bugs, faster testing, more stable releases, and less time spent on post-release fixes.
If you actively measure defect density, you can validate the effectiveness of your testing, identify key code improvement areas, and better predict how quickly you’ll be able to fix issues and release new updates.
How to measure defect density:
Example: If you find 20 defects in a 1000-line codebase, the defect density is 20/1000 = 0.02 defects per line of code.
Automation Rate measures the percentage of automated tests versus manual ones. A higher rate typically leads to faster, more consistent testing cycles across your Salesforce organization.
Why it matters: Automation rate uncovers the effectiveness of your automation strategy and points to areas where additional automation can save time, optimize resource allocation, and improve overall testing productivity.
How to measure automation rate:
Example: If you have 80 automated tests out of 100 total tests, your automation rate is (80/100) * 100 = 80%.
Test Coverage measures the percentage of your Apex code exercised by tests. It’s a fundamental metric in Salesforce development, as Salesforce requires a minimum of 75% code coverage for deployments.
Why it matters: Beyond meeting Salesforce's requirements, higher test coverage can lead to more robust applications and fewer production issues. It's especially important for complex Apex triggers and classes that handle critical business logic.
How to measure test coverage:
Example: If your tests execute 750 lines out of 1000 total lines of Apex code, your test coverage is 75%.
Test Case Effectiveness measures how efficiently your test cases find defects in your Salesforce customizations. This applies to all types of tests: Apex unit tests, integration tests, user acceptance tests, etc.
Why it matters: Effective test cases help you catch more issues before they reach production. This is crucial in Salesforce development, where a single defect could impact critical business processes across the org.
How to measure test case effectiveness:
Example: If you find 15 defects while executing 100 test cases, your test case effectiveness is (15/100) * 100 = 15%.
Pro tip: If you’re testing large applications that require a large volume of tests, then automation can help you improve your test efficiency, coverage, and accuracy. However, don’t automate every test. Choose test cases that are stable, repetitive, and time-consuming for human testers — so your team can focus on high-risk areas like complex Apex triggers, critical Salesforce integrations, and common user paths in custom Lightning pages.
Test Execution Time is how long it takes to run your suite of automated tests. In Salesforce, this includes the time to run Apex tests, as well as any automated UI or integration tests.
Why it matters: Shorter execution times mean faster feedback loops, allowing for more frequent testing and quicker iterations. This is particularly important in Salesforce CI/CD pipelines, where long-running tests can significantly slow down the release process.
How to measure test execution time:
Example: If your test suite starts at 10AM and finishes at 10:45 AM, the test execution time is 45 minutes.
MTTR measures how quickly your team can fix defects in custom code, configurations, or integrations once they're identified.
Why it matters: In Salesforce, where changes can have wide-ranging impacts, the ability to quickly identify and fix issues is crucial. A low MTTR indicates a robust system for addressing problems and minimizes the impact of defects on your users.
How to measure MTTR:
Example: If you have 5 defects with repair times of 2 hours, 3 hours, 1 hour, 4 hours, and 5 hours, your MTTR would be (2+3+1+4+5) / 5 = 3 hours.
We get it, trying to marry speed and quality in Salesforce development isn’t easy. But what if we told you there’s a better way to test in Salesforce?
In our latest guide, Is manual testing killing your release velocity? And what to do about it we cover everything you need to know about introducing comprehensive test automation into your development cycle.
Level up your Salesforce DevOps skills with our resource library.
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