$ cat case-studies/studyo-math.md

Studyo Math: Architecture Refactor for 1M+ Users

Role: Lead Android EngineerTimeline: 4 monthsPlatform: Android (Kotlin)Impact: 28% session time ↑, 1s nav ↓

The Challenge

Studyo Math, an educational app with 1M+ downloads, faced critical performance issues:

  • Slow navigation: Screen transitions took 2-4 seconds
  • Memory leaks: App crashed after 10-15 minutes of use
  • Poor engagement: Session times were 40% below industry average
  • Scaling issues: Monolithic architecture couldn't support new features

The team needed a complete architectural overhaul without disrupting the existing user base.

My Role & Approach

As the Android engineer on this project, I:

  • Conducted performance profiling to identify bottlenecks (excessive database queries, unoptimized image loading)
  • Designed a modular MVVM architecture with clean separation of concerns
  • Led implementation across 4 sprints with incremental rollout to minimize risk
  • Established automated testing (80% coverage) and CI/CD pipeline

Technical Implementation

Architecture Changes

  • MVVM + Repository Pattern: Separated UI, business logic, and data layers
  • Jetpack Compose: Migrated from XML to declarative UI for faster rendering
  • Room Database: Replaced SQLite with Room for type-safe queries and caching
  • Coroutines + Flow: Asynchronous operations with proper lifecycle management

Performance Optimizations

  • Implemented lazy loading for lesson content (reduced memory by 60%)
  • Added image caching with Coil (3x faster image loading)
  • Optimized database queries (from N+1 to batched operations)
  • Introduced WorkManager for background sync

Key Code Patterns

// Before: Blocking main thread
fun loadLessons() {
    val lessons = database.getAllLessons() // 2-3s blocking
    updateUI(lessons)
}

// After: Async with caching
viewModelScope.launch {
lessonRepository.getLessons()
.cachedIn(viewModelScope)
.collect { lessons ->
_uiState.value = UiState.Success(lessons)
}
}

Results & Impact

28%
Session Time Increase
<1s
Screen Transitions
60%
Memory Reduction
99.7%
Crash-Free Rate

Business Impact

  • User retention improved by 18% in first month post-launch
  • Play Store rating increased from 4.1★ to 4.5★
  • Development velocity increased 3x for new features
  • Reduced support tickets by 40%

Challenges & Learnings

Key Challenges

  • Data Migration: Migrating 500K+ users from old SQLite schema required careful planning and rollback strategy
  • Feature Parity: Ensuring Compose UI matched existing XML layouts pixel-perfect
  • Team Training: Upskilling team on Compose and coroutines while maintaining sprint velocity

What I Learned

  • Incremental rollout (5% → 20% → 50% → 100%) is critical for large user bases
  • Automated testing prevented 90% of regressions during refactor
  • User-facing performance wins (fast nav) matter more than internal metrics

Technologies Used

Kotlin Jetpack Compose MVVM Coroutines Room Coil WorkManager JUnit Espresso

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