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Future Optimization Recommendations

Based on the analysis of DocuSnap-Frontend's architecture and code quality, this page provides recommendations for future optimizations and improvements.

Modular Refactoring

1. Split Large Classes

Current Issue: Some classes (like ImageProcService) are too large and have multiple responsibilities.

Recommendation: Refactor large classes into smaller, focused components:

  • Split ImageProcService into specialized services: 

    class EdgeDetectionService { /* Edge detection algorithms */ }
class PerspectiveCorrectionService { /* Perspective correction */ }
class ImageFilterService { /* Image filters */ }

  • Benefits:

  • Improved maintainability
  • Better testability
  • Clearer responsibilities
  • Easier to extend with new features

2. Implement Dependency Injection Framework

Current Issue: Currently using simple manual dependency injection.

Recommendation: Adopt Dagger Hilt for dependency injection:

  • Configure Hilt in the application: 

    @HiltAndroidApp
class DocuSnapApplication : Application()

  • Provide dependencies through modules: 

    @Module
@InstallIn(SingletonComponent::class)
object AppModule {
    @Provides
    @Singleton
    fun provideDocumentRepository(
        deviceDBService: DeviceDBService
    ): DocumentRepository = DocumentRepository(deviceDBService)

    // Other dependencies
}

  • Inject dependencies into ViewModels and other components: 

    @HiltViewModel
class DocumentViewModel @Inject constructor(
    private val repository: DocumentRepository
) : ViewModel()

  • Benefits:

  • Simplified dependency management
  • Better testability
  • Consistent dependency provision
  • Scope management (singleton, activity, etc.)

3. Feature Modularization

Current Issue: All features are in a single module.

Recommendation: Implement feature modules:

  • Create separate modules for major features:
  • :feature:document - Document processing
  • :feature:form - Form processing
  • :feature:camera - Camera and image capture

  • :core:common - Shared components and utilities

  • Benefits:

  • Faster build times
  • Better separation of concerns
  • Supports dynamic feature delivery
  • Enables team to work in parallel

Error Handling Enhancement

1. Unified Error Handling Framework

Current Issue: Error handling strategies vary between modules.

Recommendation: Create a unified error handling framework:

  • Define a common Result type: 

    sealed class Result<out T> {
    data class Success<T>(val data: T) : Result<T>()
    data class Error(val error: AppError) : Result<Nothing>()
    object Loading : Result<Nothing>()
}

sealed class AppError {
    data class NetworkError(val code: Int, val message: String) : AppError()
    data class DatabaseError(val operation: String, val message: String) : AppError()
    data class ProcessingError(val stage: String, val message: String) : AppError()
    // Other error types
}

  • Use consistently throughout the application: 

    suspend fun getDocument(id: String): Result<Document> {
    return try {
        val document = deviceDBService.getDocument(id)?.toDocument()
            ?: return Result.Error(AppError.DatabaseError("getDocument", "Document not found"))
        Result.Success(document)
    } catch (e: Exception) {
        Result.Error(AppError.DatabaseError("getDocument", e.message ?: "Unknown error"))
    }
}

  • Benefits:

  • Consistent error handling
  • Better error reporting
  • Improved user experience
  • Easier debugging

2. Error Recovery Mechanisms

Current Issue: Limited error recovery options.

Recommendation: Implement robust error recovery:

  • Automatic retry for transient errors: 

    suspend fun <T> withRetry(
    times: Int = 3,
    initialDelay: Long = 100,
    maxDelay: Long = 1000,
    factor: Double = 2.0,
    block: suspend () -> T
): T {
    var currentDelay = initialDelay
    repeat(times - 1) {
        try {
            return block()
        } catch (e: Exception) {
            // Only retry certain exceptions
            if (e !is IOException && e !is HttpException) throw e
        }
        delay(currentDelay)
        currentDelay = (currentDelay * factor).toLong().coerceAtMost(maxDelay)
    }
    return block() // last attempt
}

  • User-initiated recovery options:

  • Provide retry buttons for failed operations
  • Offer alternative workflows when primary path fails

  • Save draft state to prevent data loss

  • Benefits:

  • Improved application resilience
  • Better user experience
  • Reduced support issues
  • Higher success rate for operations

Testing Coverage

1. Increase Unit Test Coverage

Current Issue: Limited unit test coverage.

Recommendation: Implement comprehensive unit tests:

  • Test ViewModels with TestCoroutineDispatcher: 

    @RunWith(JUnit4::class)
class DocumentViewModelTest {
    @get:Rule
    val instantTaskExecutorRule = InstantTaskExecutorRule()

    private val testDispatcher = TestCoroutineDispatcher()
    private val testScope = TestCoroutineScope(testDispatcher)

    private lateinit var repository: DocumentRepository
    private lateinit var viewModel: DocumentViewModel

    @Before
    fun setup() {
        Dispatchers.setMain(testDispatcher)
        repository = mockk()
        viewModel = DocumentViewModel(repository)
    }

    @After
    fun tearDown() {
        Dispatchers.resetMain()
        testScope.cleanupTestCoroutines()
    }

    @Test
    fun `loadDocuments should update state with documents from repository`() = testScope.runBlockingTest {
        // Arrange
        val documents = listOf(createTestDocument(), createTestDocument())
        coEvery { repository.getAllDocuments() } returns documents

        // Act
        viewModel.loadDocuments()

        // Assert
        assertEquals(documents, viewModel.documents.value)
        assertEquals(false, viewModel.isLoading.value)
    }
}

  • Test Repositories: 

    @RunWith(JUnit4::class)
class DocumentRepositoryTest {
    private lateinit var deviceDBService: DeviceDBService
    private lateinit var repository: DocumentRepository

    @Before
    fun setup() {
        deviceDBService = mockk()
        repository = DocumentRepository(deviceDBService)
    }

    @Test
    fun `getAllDocuments should map JSON to Document objects`() = runBlockingTest {
        // Arrange
        val jsonArray = JSONArray()
        // Add test JSON objects

        coEvery { deviceDBService.getDocumentGallery() } returns jsonArray

        // Act
        val result = repository.getAllDocuments()

        // Assert
        assertEquals(jsonArray.length(), result.size)
        // Verify mapping logic
    }
}

  • Benefits:

  • Improved code reliability
  • Regression prevention
  • Better documentation of expected behavior
  • Facilitates refactoring

2. UI Testing

Current Issue: Limited UI test coverage.

Recommendation: Implement UI tests with Compose testing:

  • Test Composables: 

    @RunWith(JUnit4::class)
class DocumentScreenTest {
    @get:Rule
    val composeTestRule = createComposeRule()

    @Test
    fun documentScreenShowsLoadingIndicator() {
        // Arrange
        val viewModel = mockk<DocumentViewModel>()
        every { viewModel.isLoading } returns MutableStateFlow(true)
        every { viewModel.documents } returns MutableStateFlow(emptyList())

        // Act
        composeTestRule.setContent {
            DocumentScreen(viewModel = viewModel)
        }

        // Assert
        composeTestRule.onNodeWithTag("loading_indicator").assertIsDisplayed()
    }

    @Test
    fun documentScreenShowsDocumentList() {
        // Arrange
        val documents = listOf(createTestDocument(), createTestDocument())
        val viewModel = mockk<DocumentViewModel>()
        every { viewModel.isLoading } returns MutableStateFlow(false)
        every { viewModel.documents } returns MutableStateFlow(documents)

        // Act
        composeTestRule.setContent {
            DocumentScreen(viewModel = viewModel)
        }

        // Assert
        composeTestRule.onNodeWithTag("document_list").assertIsDisplayed()
        composeTestRule.onNodeWithText(documents[0].name).assertIsDisplayed()
    }
}

  • Benefits:

  • Ensures UI behaves as expected
  • Catches regressions in UI behavior
  • Validates user workflows
  • Documents UI requirements

Performance Optimization

1. Image Processing Optimization

Current Issue: Image processing could be more efficient.

Recommendation: Optimize image processing algorithms:

  • Use NDK for performance-critical algorithms: 

    // In build.gradle.kts
android {
    defaultConfig {
        externalNativeBuild {
            cmake {
                cppFlags += "-std=c++17"
            }
        }
    }
    externalNativeBuild {
        cmake {
            path = file("src/main/cpp/CMakeLists.txt")
        }
    }
}

// JNI interface
external fun nativeDetectEdges(bitmap: Bitmap): Array<PointF>

  • Implement parallel processing for large images: 

    suspend fun processBitmapInParallel(bitmap: Bitmap): Bitmap = withContext(Dispatchers.Default) {
    val height = bitmap.height
    val width = bitmap.width
    val result = Bitmap.createBitmap(width, height, bitmap.config)

    // Split image into chunks for parallel processing
    val chunkSize = height / Runtime.getRuntime().availableProcessors()
    val chunks = (0 until height step chunkSize).map { y ->
        async {
            processChunk(bitmap, result, y, minOf(y + chunkSize, height))
        }
    }

    // Wait for all chunks to complete
    chunks.awaitAll()

    return@withContext result
}

  • Benefits:

  • Faster processing times
  • Reduced battery consumption
  • Better user experience
  • Support for larger images

2. Data Loading Optimization

Current Issue: Data loading could be more efficient.

Recommendation: Implement pagination and efficient data loading:

  • Add pagination to data loading: 

    @Dao
interface DocumentDao {
    @Query("SELECT * FROM documents ORDER BY last_used DESC LIMIT :limit OFFSET :offset")
    fun getDocumentsPaged(limit: Int, offset: Int): Flow<List<DocumentEntity>>
}

// In Repository
fun getPagedDocuments(page: Int, pageSize: Int = 20): Flow<List<Document>> {
    return documentDao.getDocumentsPaged(pageSize, page * pageSize)
        .map { entities -> entities.map { it.toDocument() } }
}

  • Implement efficient data loading with Paging 3: 

    @Dao
interface DocumentDao {
    @Query("SELECT * FROM documents ORDER BY last_used DESC")
    fun getDocumentsPagingSource(): PagingSource<Int, DocumentEntity>
}

// In Repository
fun getDocumentsStream(): Flow<PagingData<Document>> {
    return Pager(
        config = PagingConfig(
            pageSize = 20,
            enablePlaceholders = true,
            maxSize = 100
        ),
        pagingSourceFactory = { documentDao.getDocumentsPagingSource() }
    ).flow.map { pagingData ->
        pagingData.map { it.toDocument() }
    }
}

  • Benefits:

  • Reduced memory usage
  • Faster initial loading
  • Smoother scrolling experience
  • Better handling of large datasets

CI/CD Implementation

1. Automated Build Pipeline

Current Issue: No automated build process.

Recommendation: Implement CI/CD pipeline with GitHub Actions:

  • Create workflow file: 

    name: Android CI

on:
  push:
    branches: [ main ]
  pull_request:
    branches: [ main ]

jobs:
  build:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3

      - name: Set up JDK
        uses: actions/setup-java@v3
        with:
          java-version: '11'
          distribution: 'temurin'

      - name: Grant execute permission for gradlew
        run: chmod +x gradlew

      - name: Build with Gradle
        run: ./gradlew build

      - name: Run tests
        run: ./gradlew test

      - name: Build debug APK
        run: ./gradlew assembleDebug

      - name: Upload APK
        uses: actions/upload-artifact@v3
        with:
          name: app-debug
          path: app/build/outputs/apk/debug/app-debug.apk

  • Benefits:

  • Automated build verification
  • Early detection of issues
  • Consistent build environment
  • Improved team productivity

2. Automated Testing

Current Issue: No automated testing in the build process.

Recommendation: Add automated testing to the CI pipeline:

  • Add UI tests to CI: 

    - name: Run instrumentation tests
  uses: reactivecircus/android-emulator-runner@v2
  with:
    api-level: 29
    script: ./gradlew connectedAndroidTest

  • Add code coverage reporting: 

    - name: Generate code coverage report
  run: ./gradlew jacocoTestReport

- name: Upload coverage to Codecov
  uses: codecov/codecov-action@v3

  • Benefits:

  • Ensures tests are run consistently
  • Provides visibility into test coverage
  • Catches regressions early
  • Improves code quality

Monitoring and Analytics

1. Performance Monitoring

Current Issue: Limited visibility into app performance.

Recommendation: Implement performance monitoring:

  • Add Firebase Performance Monitoring: 

    // In Application class
FirebasePerformance.getInstance().isPerformanceCollectionEnabled = true

// Custom trace for important operations
val trace = FirebasePerformance.getInstance().newTrace("image_processing")
trace.start()
// Perform operation
trace.stop()

  • Monitor key metrics:

  • Startup time
  • Screen rendering time
  • Network request latency

  • Image processing duration

  • Benefits:

  • Identify performance bottlenecks
  • Track performance over time
  • Prioritize optimization efforts
  • Improve user experience

2. Crash Reporting

Current Issue: Limited crash visibility.

Recommendation: Implement crash reporting:

  • Add Firebase Crashlytics: 

    // In Application class
FirebaseCrashlytics.getInstance().setCrashlyticsCollectionEnabled(true)

// Log non-fatal exceptions
try {
    // Risky operation
} catch (e: Exception) {
    FirebaseCrashlytics.getInstance().recordException(e)
    // Handle exception
}

  • Add custom keys for debugging: 

    FirebaseCrashlytics.getInstance().setCustomKey("document_id", documentId)
FirebaseCrashlytics.getInstance().setCustomKey("processing_stage", "edge_detection")

  • Benefits:

  • Faster issue detection
  • Better debugging information
  • Prioritization of critical issues
  • Improved application stability

These optimization recommendations provide a roadmap for future improvements to DocuSnap-Frontend, focusing on code quality, performance, testing, and development processes. Implementing these recommendations will enhance the application's maintainability, reliability, and user experience.