The Ultimate Handbook for Salesforce Testing

Hello friend! Do you manage software testing for complex Salesforce implementations spanning countless browsers, devices and integration touchpoints?

As a testing expert with over 12+ years experience analyzing 100+ SF projects, I totally understand the headaches around tackling such intricate ecosystems.

This comprehensive handbook aims to be your guide across common Salesforce testing pain points, techniques and best practices to consider based on hard won experience.

Let‘s get started!

Introduction

Firstly, what exactly comprises Salesforce testing?

It includes validating business critical functionality, data integrity, customized enhancements and integrated systems across the entire SF platform covering:

• Complex workflows, validation rules and calculation formulae
• Intuitive UI across desktop and mobile interfaces
• Bullet proof integration with peripheral systems like ERP, CRM etc.
• Peak performance under high transaction loads
• End user acceptance catering to diverse user segments
• Overall software quality and risk coverage

Salesforce testing intersects multiple domains like functional, security, integration, interface, configuration and load testing.

This requires a diverse range of tools and skills unified under a common quality goal – ensuring flawless continuity of essential business services running within or connected via Salesforce.

Scope

Before diving into testing intricacies, let‘s broadly understand key focus areas that need validation.

Salesforce testing typically covers:

• Instance configurations e.g. user roles, authentication methods
• Custom objects, fields, layouts and relationships
• Validation rules, formula fields, flows, approval processes and assignment rules
• Visualforce pages, Lightning components, custom buttons and links
• Composite reports, dashboards and analytic snapshots
• Integrations e.g. APIs, ETL or ESB touchpoints
• Mobile and Portal interfaces + device ecosystem validation
• Key end user workflows under peak scenarios and data loads
• Overall system quality and risk coverage

As you can see the scope is quite exhaustive! So what‘s the best way to tame this testing beast?

Firstly, always start with critical business use cases instead of attempting blanket coverage. Analyze usage patterns and focus on:

• High transaction modules like cases or lead management
• Complex multi step processes like opportunity closure or order fulfillment
• Integrations with payment gateways or inventory data sync
• Customized analytics around retention or lifetime value
• New enhancements planned for market differentation

Based on priority use cases finalize phase wise test plans spanning:

1. New functionality or components
2. Integration touchpoints
3. Enhancements on existing capability
4. End to end user workflows
5. Performance benchmarks
6. Device and browser coverage
7. Peak load validation
8. User acceptance

Such segmentation lets you logically break requirements into digestable chunks for execution clarity.

Now let‘s examine popular test types employed.

Functional Testing

Validating intended behavior as per specifications lies at the heart of functional testing.

For Salesforce this means validating flawless execution of critical business logic and data computations spanning:

• Field values derived via formulae
• Conditional business logic using validation rules
• Multi step workflows and approval chains
• UI elements like custom lightning components or Visualforce pages
• SOQL queries and complex joins fetching data
• REST APIs integrating external systems or payment gateways

Some examples include:

Test Case: Validate discount percent rounding for tiered pricing

Steps:

1. As user John, add customer Acme Inc. with pricing tier Gold
2. Create new multi product order worth $5700
3. Check discount value applied = 5%
4. Validate order total = $5415

This verifies correct discount gets calculated from predefined pricing slabs.

Such test cases focused on business critical computation form the mainstay for functional validation.

Non Functional Testing

While functional testing focuses on logical correctness, non functional criteria evaluate system quality based on parameters like:

• Usability metrics
• Site responsiveness
• Scalability
• Security
• Compliance to standards
• Globalization
• Accessbility

Let‘s see some examples:

Test Case: Measure time taken for record search across user segments

Steps:

1. Raise 100 transaction records across opportunities, cases and leads
2. Record time for manager to run search based on date and keyword filters
3. Record executive running similar search without filters
4. Check if difference between average search times falls under 500 ms threshold

This allows benchmarking interface efficiency between user profiles.

Similarly compliance around password policies, site color contrast ratios, multi currency support etc can be validated through focused test cases.

Now let‘s tackle some common pain points around Salesforce testing.

Cross Browser Testing

With dynamic HTML, client side rendering and complex javascript UIs, ensuring pixel perfect experiences across Safari, Chrome, Firefox and legacy browsers requires intricate testing.

If the org uses Lightning, here are some key testing considerations:

• Component based responsive UIs render differently across viewports
• Browser security policies affect functionality e.g. pop up blockers
• Varying standards support creates CSS and layout failures needing fixes
• Each browser engine handles JavaScript execution differently causing errors
• Cookies and cache policies alter expected state during workflows

So beyond functional flows, remember to test diverse browser driven paths e.g:

• Refresh record page mid workflow to check state consistency
• Disable javascript on payment pages to validate progressive enhancement
• Mask user agents to simulate deprecated browser versions
• Override geolocation API for location based personalization
• Test each OS and hardware rendering combination

Based on test outcomes, using browser based feature controls help stabilize experiences e.g:

// Target only Chrome  
@supports (-webkit-background-clip: text) {
  button {  
    background-clip: text;
    color: transparent; 
    background-image: linear-gradient(to right, #0076ff, #ed1b24);
  }
}

This backed by Automated Browser Testing across 1000+ configurations using frameworks like Selenium, Playwright and BrowserStack is invaluable for catching rendering defects early.

Mobile Testing

If your business relies on field agents or reps using Salesforce mobile apps, testing across real iOS and Android devices is critical given the hardware and OS fragmentation.

Some tips for reliable mobile testing:

• Define priority device list mapping to target user base
• Automate install, upgrade and settings validation on real devices
• Check connectivity usage through network traffic shaping
• Test different mobile gesture actions like swipe, scroll, zoom etc.
• Rotate devices to landscape modes for orientation support
• Retry network calls made on flaky cellular connections
• Check battery drainage running high usage workflows
• Validate offline caching and state consistency
• Test across both OS tablets beyond just phones
• Examine API traffic with proxy tools

Building a CI pipeline around Appium test automation running on 2000+ real mobile devices on BrowserStack brings confidence for enterprise mobile app rollouts.

Integration Testing

With numerous backend integrations to ERP, payment gateways, marketing platforms etc. testing end to end scenarios covering:

• Bidirectional data sync
• Authentication across domains
• Communication protocols
• Error handling and rollbacks
• Logging and reporting

becomes necessary to validate fault tolerance.

Let‘s see an example API testing scenario:

Title: Sales analytics data integration

Steps:

1. Configure secure OAuth authentication for Analytics Cloud connector
2. Map fields from Sales Cloud into dataset extraction
3. Initiate batch API call to fetch last 7 days updated data
4. Validate 20,000 records extracted without truncation
5. Assert duplicate checking logic working on datasets
6. Handle connection timeouts through re-initiation automatically
7. Log warning emails if no records returned from source

Here extensive boundary case injection reveals platform stability.

You can set up such test automation suites using Postman Collections driving SOAP UI test cases for example.

Load and Performance Testing

Salesforce orgs tend to accumulate enormous data volume given their central role across domains like:

• Order management
• Campaign analytics
• Field service history
• Case management
• Lead scoring

Validating system stability and response times under peak traffic and stressed data loads prevents chaotic outages.

Some techniques I have found useful over the years include:

• Injecting sudden traffic spikes through bots or scripts
• Isolating heavy modules like search and running exhaustive test cases
• Simulating DDoS attacks using open source tools
• Updating batch sizes 10x over regular values
• Generating flawed data through randomizers
• Enabling caching and checking performance gain
• Profiling code executing during key transactions

These reveal platform bottlenecks helping refine limits around:

• Maximum records per object
• Concurrent API limits
• Batch job sizes
• Automation execution timeframes
• Peak transations per hour

Environment Setup

To enable reliable test execution leveraging separated SF sandboxes for test automation isolated from ongoing development is key.

Version Control

Backing test assets under source control enables traceability. This covers:

• Manual test cases
• Test data scripts
• Automation suites
• Browser images
• Config documents
• Device inventories

Popular options include Git, SVN, Azure DevOps and BitBucket.

Continuous Integration

Running regression packs against code changes quickly spots defects through CI enabled workflows.

For example on commiting an Apex trigger, Jenkins could:

1. Deploy code to test org
2. Execute associated unit tests
3. Run regression test suite
4. Notify results

Frequent build -> test -> release sprints across sandbox environments prevent longer feedback loops.

Service Virtualization

When reliant on downstream systems, replicating dependencies using mocks and stubs improves reliability.

For example staging an exact copy of the payment gateway with preregistered responses allows testing invalid scenarios without impacting vendors.

Powerful options include WireMock, Hoverfly and Mountebank.

Test Reporting

Central dashboards around key metrics provide visibility into testing effectiveness covering:

• Test cycles executed
• Test case coverage and gaps
• Defects slipped by priority
• Automation pass percentage
• Lead time per test run
• Platform uptime

Leverage out of the box Salesforce test results or integrate external ALM tools like qTest, Practitest or TestRail.

Test Data Management

Managing test data at scale is always tricky with needs for:

• Anonymizing direct copies of production data
• Masking sensitive information
• Retaining dataset diversity matching source
• Bulk loading multi GB datasets
• Isolating mutations from upstream
• Handling test case correlations

Utility services like Delphix and Informatica offer Data Masking and Test Data Management solutions specifically helping overcome these exact challenges.

Defect Management

Despite extensive test coverage, some defects inevitably slip through requiring:

• Bug tracking – Capture environment, steps to reproduce and logs
• Root causing – Map related events, invalid data leading to failure
• Prioritization – Categorize severity, user impact and escalate
• Retesting – Validate fixes before closure
• Trend analysis – Determine spike areas by type and module

Integrating reporting across QA, development and production monitoring ensures end to end traceability on defect resolution.

Best Practices

Let‘s conclude with some key guidelines worth remembering:

• Start testing early, not just UAT at the end
• Focus test effort on critical 20% delivering 80% value
• Develop libraries around reusable test steps, functions and workflows
• Automate repetitive but business critical validation scenarios
• Follow shift left principle integrating QA into agile dev sprints
• Test across message buses, asynchronous flows and error handling
• Setup cloud based device labs for anytime anywhere access
• Mask test data early avoiding policy violations
• Follow risk based model balancing test depth and priority

These practices harnessed in unison help tame convoluted Salesforce testing complexity at scale and deliver flawless business continuity.

So in summary, I hope this guide served as a practical handbook around successfully testing intricate Salesforce implementations based on real world expertise. Feel free to reach out to me for any specific queries!