Testing is an essential part of software development, and automated Salesforce testing is no exception. Salesforce provides a range of testing options that can be used to ensure the integrity, performance, and accuracy of your applications. The goal of this guide is to provide an overview of automated Salesforce testing, the different types of tests available, and how they can be used in the context of a Salesforce Lightning Migration.
What Is Automated Salesforce Testing?
Source: mabl.com
Automated Salesforce testing is a process that uses specialized tools to simulate user behavior on a system. These tests are designed to check the functionality and performance of an application or system in its actual environment by performing scripted tasks such as entering data, clicking on buttons and links, navigating through menus, and so on. The advantage of using automation for software testing is that it allows developers to quickly identify issues before they become problems for end users.
Types Of Automated Tests For Salesforce
There are several types of automated tests that can be used for Salesforce applications:
- Unit Tests: Unit tests verify individual components or functions within an application in isolation from other components or functions. This type of test checks for errors within the code itself by executing specific functions or commands in the codebase independently from other components or functions.
- Integration Tests: Integration tests are used to verify how different parts of an application interact with each other when combined together into one system. This type of test checks if data can flow between two different systems successfully and if any errors occur when these systems communicate with each other via APIs or web services.
- Smoke Tests: Smoke tests are quick and easy tests that are used to check if all major functionality works after making changes or updates to an application. This type of test is often done right after new code is deployed into the production environment so any major bugs can quickly be identified before they cause any serious problems with end users’ experience with the system.
- Regression Tests: Regression tests are used to verify if existing functionalities continue to work properly after making changes or updates to the system or introducing new features to it. This type helps catch any potential unintended effects caused by changes made during the development cycle and assures that existing functionality remains intact without introducing any errors into them.
- User Acceptance Tests (UAT): UATs are often performed by end-users before releasing a system into the production environment. This type focuses on verifying if user experience meets expectations set forth by developers when designing a product. It also helps identify whether all features specified in requirements documents have been implemented correctly at the time when the product is ready for release.
Source: testim.io
Using Automation For Salesforce Lightning Migration
Salesforce Lightning Migration requires extensive testing before being released into the production environment as it involves changing UI/UX completely across all devices with an extensive amount of work involved in correctly migrating existing data over to the lightning platform while ensuring all rules associated with processes remain intact. To make sure lightning migration goes smoothly, robust automation testing should be employed.
Various types like unit, integration, smoke, regression & UAT tests can be utilized across multiple platforms like mobile & desktop interfaces depending on needs & requirements involved during the migration process as well as goals desired out of the product/system overall. By combining automation with manual QA efforts, companies can ensure the lightning migration process runs smoothly while meeting expectations set forth before beginning the process while catching any unexpected issues quickly & efficiently along the way helping improve user experience overall in the long run once migrations complete successfully.
