Week 4 Testing, CI/CD & Deployment Setup #

Project name: VoiceDiary

Code repository: link

VoiceDiary is an AI-powered voice journaling tool that analyzes tone, emotion, and key themes in spoken entries. It generates personalized emotional insights and well-being suggestions based on recorded reflections.

Team #

Frontend #

Responsible: Dziyana Melnikava, Anastasia Kuchumova

Link to frontend contribution: CLICK TO SEE

• Unit tests for critical frontend components are wtitten.
• Component for Analysis Output enhanced according to new ML model.
• Authentication is established.
• Feedback component was created.
• Main and User Profile pages are created.
• Custom calendar is implemented.

Unit Testing Areas #

🎤 AudioRecorder Component Tests #

• Initial UI Rendering:
  Ensures microphone icon (MicIcon) is visible on initial load, verifies that recording controls like “Pause” or “Stop” are not displayed unless recording starts.
• Permission Denied Banner:
  When microphone permission is ‘denied’, the component shows a warning icon and an alert message: “Microphone access is blocked”.
• Active Recording State:
  Shows recording controls (Pause, Stop icons) and the recording timer when recording starts.
• Post-recording Loading State:
  Displays a loading message indicating voice recording is being analyzed.
• Save/Delete UI After Recording:
  When audioBlob exists (indicating recording finished), the component shows Save and Delete buttons with corresponding labels.
• Delete Confirmation Trigger:
  Clicking the delete icon triggers the handleDeleteClick function, initiating delete confirmation.
• Stop Recording Action:
  Clicking the stop icon calls the stopRecording function, verifying the stop recording interaction.

⭐ FeedbackWidget Component Tests #

• Initial Render:
  Renders the feedback question and instruction text.
• Display of Rating Options:
  Verifies all rating buttons with emojis and labels are displayed.
• Submitting a Rating:
  Checks that clicking a rating calls the onSubmit handler with the correct value.
• Thank You Message After Submission:
  Confirms the thank-you message appears and the question disappears after rating submission.
• Hover Effect on Ratings:
  Applies active CSS class when hovering over a rating button.
• Hover Leave Effect:
  Removes active CSS class when mouse leaves a rating button.

📊 RecordingCard Component Tests #

• Rendering Behavior with Null Result:
  Verifies that the component renders nothing when the result prop is null.
• Full Rendering with Valid Result:
  Checks that all main sections (emotion, summary, insights, coping strategies, recommendations, footer) render correctly for a valid result object.
• Emotion Pill Styling:
  Tests that the emotion label displays with the correct CSS class depending on the emotion type (positive, negative, aggressive, neutral).
• Rendering Multiple Key Triggers:
  Confirms that multiple key triggers are rendered correctly when present in the data.

🌊 WaveAnimation Component Tests #

• Audio Initialization on Recording Start:
  Verifies that when the component mounts with isRecording=true, it requests microphone access (navigator.mediaDevices.getUserMedia) and creates an AudioContext.
• Graceful Handling of getUserMedia Errors:
  Simulates permission denial or error during microphone access request and confirms that the error is caught and logged via console.error without crashing.
• Animation Frame Cleanup on Unmount:
  Confirms that ongoing animation frames requested via requestAnimationFrame are properly cancelled on component unmount to prevent memory leaks or unnecessary processing.

✅ Test Cases #

Backend #

Responsible: Olesia Novoselova, Danil Davydyan

Link to backend contribution: CLICK TO SEE

• User authentication implemented using HTTP-only cookies with a 30-day expiration period.
• Secure password handling added: user passwords are hashed at the service layer before storage.
• Unit tests written for critical service and repository logic.
• Integration tests developed for key API endpoints to verify end-to-end functionality.
• CI/CD pipeline and Docker Compose setup completed for streamlined development and deployment.

Unit & Integration Testing Areas #

🔑 Authentication & Session Management Tests #

• User Registration:
  Verifies that new users are registered with hashed passwords and stored securely in the database.
• User Login:
  Ensures users can log in with valid credentials, and receive a secure HTTP-only session cookie.
• Session Validation:
  Checks that endpoints requiring authentication reject requests with missing or invalid session tokens.

🗄️ Service & Repository Layer Tests #

• User Service:
  Tests user creation, password hashing, session creation, and user retrieval by login or session token.
• Record Service:
  Verifies saving, fetching, and retrieving records by user and record ID.
• Repository Functions:
  Ensures correct SQL operations for users, sessions, and records, including error handling for not found and constraint violations.

🌐 API Integration Tests #

• /users/register:
  Confirms successful registration and error handling for duplicate users.
• /users/login:
  Validates login flow, session cookie issuance, and error responses for invalid credentials.
• /me:
  Checks that authenticated users can retrieve their profile info, and unauthenticated requests are rejected.
• /records/upload:
  Tests file upload endpoint for authentication and correct error handling.
• /users/:userID/records & /records/:recordID:
  Verifies correct responses for valid, invalid, and non-existent users/records.

⚙️ CI/CD & Deployment #

• CI/CD Pipeline:
  Automated testing and deployment pipeline configured for backend service.
• Docker Compose:
  Multi-service orchestration for backend, database, and ML service for local development and

✅ Test Cases #

Test Cases output is available here: CLICK HERE

ML #

Responsible: Dzhamilia Fatkullina, Elina Kuzmichyova

Link to ML contribution: CLICK HERE

Individual commitments #

Plan for Next Week #

ML #

• Do emotion recognition model orchestration
• Conduct research on additional feature models

Frontend #

• Improve UI/Ux
• Implement new features that will be introduced by ML team
• Collaborate with backend team on connecting calendar to database

Backend #

• Implement logic for loading users’ avatars
• Modification of the go->python contract for more optimal use of ml models and easier deployment
• Setting up the test environment

Confirmation of the code’s operability #

We confirm that the code in the main branch:

• [✓] In working condition.