← Salesforce Interview Insights

Salesforce·Software Engineer·Online Assessment (OA)·Intermediate

IntermediatePrefer not to say
Jun 2026Remote

Summary

Salesforce gave me a frontend TypeScript exercise that covered three things at once: fixing broken snapshot tests, writing new ones, and then refactoring messy conditional logic into something cleaner. A lot to juggle in one session, and they wanted you to talk through the design thinking too.

Questions Asked (3)

Q1

You're given TypeScript code full of if/else chains and duplicated logic. Read the existing snapshot tests, identify which ones are failing, and fix them.

Technical Trade-offsAPI & Integrations
Author's notes

The snapshot tests were actually a decent breadcrumb trail into what the code was supposed to do.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Start by running the test suite to see which snapshot tests fail, then analyze the diffs to understand the expected vs. actual output. Refactor the if/else chains and duplicated logic into cleaner, reusable functions while ensuring the snapshot tests pass, and update snapshots only if the changes are intentional and correct.

Pro tip: Before changing any code, use git to commit the current state so you can easily revert if needed. Also, treat snapshot tests as a safety net—if a snapshot fails, verify whether the change is a bug or an intended improvement before updating it.

1. Run tests and identify failures

Execute the test suite to see which snapshot tests fail. Note the specific test names and the diffs between expected and received output.

2. Analyze the code and failures

Examine the failing tests and trace the logic in the TypeScript code. Identify the if/else chains and duplicated logic that cause the discrepancies.

3. Refactor for clarity and correctness

Extract duplicated logic into functions, replace if/else chains with clearer patterns (e.g., switch, polymorphism, or lookup tables), and ensure the behavior matches the expected snapshots.

4. Re-run tests and update snapshots if needed

After refactoring, run the tests again. If failures persist, debug further. If the new output is correct, update the snapshots intentionally.

5. Verify and communicate

Ensure all tests pass and the code is cleaner. Be prepared to explain your changes, trade-offs, and why the updated snapshots are correct.

Key Points to Mention

  • Understanding snapshot testing and how to interpret diffs
  • Refactoring techniques: extracting functions, replacing conditionals with polymorphism or strategy pattern
  • Importance of running tests frequently and using them as a safety net
  • When to update snapshots vs. fix code (intentional vs. unintentional changes)
  • Maintaining code readability and reducing duplication
  • Communicating trade-offs between quick fixes and long-term maintainability

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.

Q2

Extend the test suite to cover cases not already tested in the existing snapshots.

Technical Trade-offs
Author's notes

I added a few edge cases around the conditional branches but honestly I wasn't sure how thorough they wanted me to be.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Start by clarifying the scope of the existing snapshots and the component under test, then systematically identify untested edge cases, error paths, and boundary conditions. Prioritize additions based on risk and business impact, and propose a concrete plan to implement and validate the new tests.

Pro tip: Mention that snapshot tests often miss dynamic or conditional rendering paths; proposing targeted tests for those gaps shows you understand both testing strategy and real-world failure modes. Also, suggest using mutation testing to validate that new tests actually catch regressions.

1. Clarify scope and existing coverage

Ask questions to understand what the snapshots currently cover, the component's responsibilities, and any known limitations. Review the snapshot files and related test code to map covered vs. uncovered scenarios.

2. Identify untested cases

Enumerate edge cases, error states, conditional branches, user interactions, and data variations not represented in snapshots. Consider boundary values, null/undefined inputs, and asynchronous behavior.

3. Prioritize based on risk and impact

Rank the identified cases by likelihood of failure and potential impact on users or business logic. Focus on high-risk areas first, such as critical user flows or complex conditional logic.

4. Propose concrete test additions

Describe specific test cases to add, including the expected behavior and how they complement existing snapshots. Suggest using a mix of snapshot and assertion-based tests where appropriate.

5. Validate and iterate

Explain how you would run the new tests, ensure they fail before the fix (if applicable), and integrate them into CI. Mention monitoring test coverage and flakiness.

Key Points to Mention

  • Snapshot tests are good for detecting unintended UI changes but poor at covering logic branches and edge cases.
  • Use code coverage tools to identify untested lines and branches, but don't rely solely on coverage metrics.
  • Consider property-based testing or mutation testing to uncover gaps that example-based tests miss.
  • Test error boundaries, loading states, and empty states that snapshots often omit.
  • Ensure new tests are deterministic and don't introduce flakiness; mock external dependencies appropriately.
  • Collaborate with the team to align on testing strategy and avoid redundant or brittle tests.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.

Q3

Refactor the TypeScript so that the conditional logic is replaced by a rule table lookup. Explain which design pattern this represents and why you chose it.

Technical Trade-offsSystem DesignAlgorithms & Data Structures
Author's notes

This was the meat of it.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

First, identify the conditional logic and extract the conditions and outcomes into a data structure like a map or array of rules. Then, replace the if/else or switch with a lookup function that evaluates the rules in order. Finally, explain that this is the Strategy pattern (or Table-Driven Method) and justify why it improves maintainability, extensibility, and readability.

Pro tip: Mention that rule tables can be externalized to configuration files or databases, enabling business users to modify rules without code changes—a key advantage in enterprise systems like Salesforce.

1. Identify and Extract Conditions

Locate the conditional logic and list all condition-outcome pairs. Ensure you capture the order of evaluation and any default behavior.

2. Design the Rule Table

Choose a data structure (e.g., array of objects, Map) to represent rules. Each rule should include a condition (predicate) and an action (result or function).

3. Implement the Lookup Mechanism

Write a function that iterates through the rules, evaluates each condition, and returns the corresponding action. Handle no-match cases with a default.

4. Refactor and Test

Replace the original conditional logic with the lookup. Write unit tests to ensure behavior is unchanged and edge cases are covered.

5. Explain the Pattern and Trade-offs

Articulate that this is the Strategy pattern (or Table-Driven Method). Discuss benefits like separation of concerns, ease of adding rules, and potential performance considerations.

Key Points to Mention

  • Strategy pattern: encapsulates interchangeable algorithms and makes them selectable at runtime.
  • Table-driven method: a technique to replace complex conditionals with data-driven lookup.
  • Open/Closed Principle: new rules can be added without modifying existing code.
  • Readability and maintainability: rule tables are easier to understand and modify than nested conditionals.
  • Performance: lookup may be O(n) but can be optimized with indexing or hashing if needed.
  • Externalization: rules can be stored in config or database for dynamic updates.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.