Apex tests are a deployment requirement, but treating them as a code-coverage tax produces fragile Salesforce applications. Good tests prove behavior: the expected record changes occur, invalid paths fail correctly, permissions are respected, bulk operations work, and future refactoring does not silently change the contract. The current Salesforce Platform Developer<\/a> role therefore treats testing as part of implementation design.<\/p>\n The wider Salesforce certifications<\/a> ecosystem also treats safe release behavior as a shared platform responsibility. Salesforce production deployments that include Apex require successful tests and minimum code coverage. The platform commonly requires at least 75% aggregate coverage, and specified-test deployments impose coverage requirements on the classes and triggers in the package. Coverage is necessary, but behavior matters more.<\/p>\n Tests become readable documentation when method names describe the scenario and expected result. Names such as closesCase_whenRequiredFieldsPresent make failures easier to diagnose than testMethod1. Organize setup so the business condition is visible; future developers should understand the rule from the test without opening every helper class.<\/p>\n A strong test creates the conditions, invokes the behavior, and asserts the business result. It should not depend on internal variables or exact line structure that may change during refactoring.<\/p>\n For example, test that a discount above a threshold creates an approval request rather than asserting which private helper method was called. Outcome-focused tests are more durable.<\/p>\n Test factories should balance reuse with clarity. A single mega-factory with dozens of optional parameters can hide important setup just as badly as duplicated record creation. Provide sensible builders for common entities, then override only the fields relevant to the scenario. The goal is fast, deterministic setup that still makes the test’s intent obvious.<\/p>\n Tests should create their own records instead of depending on production data. Factories or builder methods can create reusable account, contact, opportunity, or custom-object scenarios while keeping each test readable.<\/p>\n The techniques behind dummy data generation<\/a> are useful conceptually: representative variation exposes assumptions that one perfect record hides.<\/p>\n Negative tests should assert the error contract. If code intentionally throws a custom exception or adds an error to a record, confirm the message or outcome that callers rely on. This prevents later refactoring from replacing a meaningful business error with a generic failure that is harder for users and integrations to handle.<\/p>\n Happy-path tests prove that valid operations succeed. Negative tests prove that invalid data, missing permissions, unexpected states, or exceptions are handled correctly. Boundary conditions often matter most: zero values, nulls, maximum sizes, duplicate keys, and status transitions.<\/p>\n Tests should assert the exact business consequence. A test that executes without throwing but never checks the database can pass even when the logic does nothing useful.<\/p>\n Bulk tests are especially important for code invoked by triggers because one transaction can contain mixed records. Create a batch where only some records meet the condition and assert that only those records change. This exposes logic that accidentally uses the first record’s state for the entire batch.<\/p>\n If code can be invoked through imports, APIs, or bulk DML, tests should process collections rather than only single records. Bulk tests reveal queries in loops, repeated DML, recursion, and incorrect assumptions about record ordering.<\/p>\n This connects directly to the performance discipline in scalable system design<\/a>.<\/p>\n Use startTest and stopTest once per test method around the behavior that matters. They are not a substitute for efficient code; they create a clearer measurement and execution boundary. Keep heavy test-data construction outside the window so the code under test receives a fresh set of relevant governor counters.<\/p>\n These methods reset many governor counters for the code inside the test window and allow queued asynchronous work to complete when stopTest is reached. They make it easier to separate test-data setup from the transaction being measured.<\/p>\n Use them deliberately rather than mechanically. The setup phase should prepare state; the test window should perform the operation whose behavior matters.<\/p>\n For Batch Apex, verify finish behavior and results across multiple scopes where practical. For Queueable jobs, assert the persisted outcome after stopTest. If asynchronous code chains additional work, design tests around the supported execution behavior and isolate responsibilities so one test does not depend on an uncontrolled sequence of jobs.<\/p>\n Queueable, Batch, Scheduled, and future work executes differently from synchronous Apex. Tests should enqueue the work inside the startTest\/stopTest window and then assert the resulting records or state after stopTest.<\/p>\n Testing the final result is stronger than merely asserting that a job ID was returned.<\/p>\n Persona-based testing should focus on application behavior under expected access, while dedicated security review confirms CRUD, field-level, and sharing enforcement. A test running as a low-privilege user can reveal assumptions, but developers still need to understand system context and explicit enforcement mechanisms used by Apex.<\/p>\n RunAs can help test behavior under different users, but developers must understand what it does and does not enforce. Tests should cover sharing expectations, permission-sensitive paths, and whether server-side code exposes data beyond the intended user context.<\/p>\nTests should describe outcomes, not implementation details<\/h3>\n
Test data should be isolated and intentional<\/h3>\n
Positive and negative paths both need assertions<\/h3>\n
Bulk tests protect trigger and service design<\/h3>\n
Test.startTest and Test.stopTest isolate the action under test<\/h3>\n
Asynchronous code needs explicit verification<\/h3>\n
Security-sensitive code deserves persona-based tests<\/h3>\n