Advanced interview questions in Mobile Dev, page 5
Difference between remember and rememberSaveable
Remember survives recompositions only; rememberSaveable uses Bundle state for config changes and process death; use for UI state after recreation.
`remember` vs. `rememberSaveable`: When and why to use each?
Tests understanding of state survival in Compose. A good answer contrasts remember (for composition) with rememberSaveable (for activity recreation/process death), explaining its use of the Bundle mechanism. A red flag is confusing the two lifecycles.
remember vs. rememberSaveable: When and Why to Use Each
Tests understanding of Compose state survival. remember is for recomposition scope. rememberSaveable survives activity recreation and process death via a Bundle, requiring custom Savers for complex types. Red flag: saying remember survives rotation.
Optimistic UI updates for actions
Update UI immediately on the assumption of success, send the request, then confirm or roll back on failure.
Diagnose Compose recomposition issues and explain lambda stability
Tests Compose skipping and stability. Strong answers name recomposition counts, compiler metrics, and immutable state, then explain unremembered lambdas create new instances and prevent skipping.
How do you diagnose and fix excessive recomposition in Jetpack Compose?
This tests your grasp of Compose's stability system. First, use Layout Inspector to find high-recomposition areas. Then, enable and analyze the Compose compiler report to diagnose unstable parameters (like List) or lambdas.
How do you diagnose and fix excessive recomposition in Jetpack Compose?
This tests your understanding of Compose's stability system for performance. Use the Layout Inspector and Compiler Metrics to find unstable composables, then fix them with immutable data types and stable lambdas.
Offline data persistence and mutation queue
Persist reads to local storage, store mutations in a durable queue with client ids and status, drain and reconcile on reconnect via NetInfo.
Apollo's normalized cache
Apollo flattens query results into entities keyed by type plus id, so one object is stored once and shared, updating everywhere at once.
Optimize a slow NSFetchedResultsController screen
Set fetchBatchSize so rows load in pages, use relationshipKeyPathsForPrefetching to avoid per-row faulting round trips, and add indexes matching sort and predicate to make queries fast.
Bulk-import large JSON into Core Data efficiently
Use NSBatchInsertRequest to write rows directly to the store, bypassing context object materialization, for huge memory and speed wins; limitation is it skips validation, relationships, and does not notify…
Custom fade-and-scale transition with PageRouteBuilder and GoRoute
Tests bridging imperative transitions to declarative routers. Use PageRouteBuilder with FadeTransition and ScaleTransition, set globally in theme or per route via GoRoute pageBuilder with CustomTransitionPage. Red flag: omitting child rebuilds the page.
Design offline-first sync and conflict resolution
Queue local mutations with timestamps and sync state, push and pull deltas using a change token or updatedAt cursor, and resolve conflicts with a chosen policy like last-write-wins or field-level merge.
Designing a native map UI component
Wrap each platform's native view, expose props mapped to native setters and events as bubbling callbacks, unify behind one JS API.
Responsive layout across form factors
Drive layout from dimensions and breakpoints via useWindowDimensions, react to orientation changes, avoid hardcoded OS checks.
How would you architect two source Flows from ViewModel to data layer?
This tests merging parallel async streams into one reactive state. A strong answer uses combine on two cold repository Flows, exposes one UI state Flow from the ViewModel, and maps failures to error states. Red flag: using two coroutines mutating shared state.
Combine two network sources using Coroutines and Flow
Tests your grasp of async data combination and state management. A good answer uses Flow.combine in a ViewModel, fed by a Repository, emitting a sealed class for UI state (Loading, Success, Error). A red flag is trying to combine state in the UI layer itself.
Immutable bloc state versus mutable ChangeNotifier
Immutable gives predictable diffs, easy debugging and replayability at the cost of boilerplate; mutable is terse but error-prone.
How do you navigate between feature modules without direct dependencies?
This tests architectural decoupling in multi-module Android apps. A great answer describes a shared navigation contract or deep-link router that lets features stay independent. Recommending direct Gradle dependencies between features is a major red flag.
Navigate between feature modules without direct dependencies?
Tests dependency inversion in modular apps. Answer by defining navigation interfaces in a shared module, implementing them in the :app module, and using DI to connect them. A red flag is suggesting direct module dependencies or using reflection for navigation.
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