TypeScript Developer OOPS Concepts Interview Guide

Choose composition when the relationship is about using a capability rather than being substitutable for the base type. Delegate behind a small interface and keep invariants local. Inheritance can be appropriate, but test that derived behavior honors the expectations of callers using the base abstraction.

Check your understanding: Replace the implementation behind an interface and run the same contract tests.

Common trap: Using inheritance only to avoid copying a few lines.

Concept reference: Dev.java: language, collections and JVM learning paths

Not necessarily. Encapsulation protects meaningful invariants and exposes valid operations, rather than merely making fields private. Model state transitions so callers cannot construct invalid combinations, and keep representation details from leaking through mutable references.

Check your understanding: Attempt an invalid transition through the public API.

Common trap: Equating private fields with a complete domain model.

Concept reference: Dev.java: language, collections and JVM learning paths

Look for implementers that must provide meaningless operations or callers that depend on methods they never use. Split responsibilities around real usage while avoiding one interface per line of code. Test consumers against alternate implementations to expose hidden assumptions.

Check your understanding: Implement a second legitimate provider without no-op methods.

Common trap: Designing an interface from one implementation’s internals.

Concept reference: Dev.java: language, collections and JVM learning paths

No. Type annotations describe compile-time expectations; they do not validate a network response. Start external data as unknown, validate its shape and constraints, and only then expose a trusted application type. Distinguish malformed responses from legitimate empty data so callers can handle both.

Check your understanding: Feed a missing field, wrong type and unexpected enum value through the boundary.

Common trap: Using a type assertion as a runtime security check.

Concept reference: TypeScript: narrowing

Use a union with a literal status field and data appropriate to each state. Narrow by that field before reading the payload. An exhaustive switch can make adding a new state a compile-time task rather than leaving forgotten branches. Runtime input still needs validation before it enters the union.

Check your understanding: Add a new status and ensure all rendering branches must handle it.

Common trap: Several independent booleans that allow success and failure simultaneously.

Concept reference: TypeScript: narrowing

The assertion suppresses a compiler concern but adds no runtime check. Handle the absent user explicitly, then narrow the value before use. Preserve the distinction between not found, forbidden and unavailable at the service boundary without leaking another user’s data.

Check your understanding: Test an absent record and an authenticated caller who does not own it.

Common trap: Assuming authentication makes every looked-up record accessible.

Concept reference: OWASP: authorization checks

First, identify technical constraints and define measurable service objectives. Next, trace values through scope, task queues, type boundaries and observable side effects. Contrast architectural trade-offs across reuse, clarity, extensibility and accidental complexity, explicitly mitigate the risk of a partially deployed reader cannot understand the new representation, and confirm system stability using a compatibility contract, expand-and-contract rollout and rollback rehearsal.

Common trap: Reaching for a specific library or framework before defining constraints, failure envelopes, and automated verification criteria.

Prioritise the failure mode exhibiting the highest user blast radius and lowest observability. Formulate an explicit containment boundary, implement idempotent retries with jitter, and establish an automated rollback threshold. Verify resilience through a compatibility test matrix and a staged rollout metric.

Common trap: Relying on passive monitoring dashboards without defining explicit error-budget alerts, rollback triggers, and verified recovery procedures.

Structure the response using Context-Decision-Tradeoff-Result: articulate the business and technical constraints, compare viable alternatives, explain the implementation (trace values through scope, task queues, type boundaries and observable side effects), and document the accepted trade-off. Provide concrete proof: a focused unit test, dependency boundary and refactoring comparison.

Common trap: Speaking only in high-level abstractions or team accomplishments without detailing your direct implementation decisions, trade-offs, and measured results.

Formulate a falsifiable hypothesis from observable telemetry before altering configurations. Then inspect task ordering, retained references, type assumptions and a minimal runtime reproduction. Isolate the defect to the smallest reproducible boundary, validate root cause with evidence, and confirm full resolution using a trace, a minimal reproduction and a regression test.

Common trap: Applying speculative fixes or restarting services blindly without establishing an observable signal connected to a falsifiable hypothesis.

Produce a typed boundary test with an event-order trace and bundle comparison. Document baseline assumptions, technical mechanism (trace values through scope, task queues, type boundaries and observable side effects), rejected alternatives, bounded failure envelopes, and deterministic pass criteria. Supply reproducible verification via queue-depth metrics, bounded retry behaviour and a recovery drill.

Common trap: Presenting architecture diagrams or slides lacking automated unit/integration tests, observable metrics, or automated rollback configurations.