How itsluuis/first-order-logic works
This is a browser-based symbolic-logic learning app. A student can build a molecular proposition, convert it to a well-formed formula (FBF), or enter an FBF for natural-language reconstruction; the app also evaluates truth tables and offers four timed practice games. The main controller coordinates these workflows, with local profile/settings persistence and a local student model supporting practice and Moli’s contextual tutoring. README capabilities are included where implementation excerpts were unavailable; the graph omits uncertain wiring for those unsampled areas.
Main entry points: app.js App controller · practiceEngine.js Four-game engine · mascotController.js Moli controller · studentModel.js Student learning model
Components 15
Application workflows
- App controller
js/app.js - Visual builder
js/app.js - Inverse workflow
js/app.js
Logic tools
- FBF parser and AST
js/logic/ast.js - Random generators
js/logic/generators.js - Natural-language mapping
js/logic/naturalLanguage.js - Truth-table engine
js/logic/truthTable.js
Practice and learning
- Practice interface
js/practice/practiceView.js - Four-game engine
js/practice/practiceEngine.js - Student learning model
js/ml/studentModel.js - Neural network
js/ml/neuralNet.js
Moli tutor
- Moli controller
js/mascot/mascotController.js - Moli OLED view
js/mascot/mascotView.js
Local state
- Profiles and settings
js/storage.js
Other components
- Student
Connections 24
- Student → App controller: uses app
- App controller → Profiles and settings: reads and writes
- App controller → Visual builder: routes to
- App controller → Inverse workflow: routes to
- App controller → Truth-table engine: requests evaluation
- App controller → Practice interface: initializes
- App controller → Four-game engine: initializes
- App controller → Moli controller: initializes
- Visual builder → Random generators: generates formulas
- Visual builder → Natural-language mapping: translates proposition
- Visual builder → FBF parser and AST: formats FBF
- Inverse workflow → FBF parser and AST: parses FBF
- Inverse workflow → Random generators: generates FBF
- Inverse workflow → Natural-language mapping: reconstructs proposition
- Truth-table engine → FBF parser and AST: reads AST
- Four-game engine → FBF parser and AST: parses and formats
- Four-game engine → Truth-table engine: evaluates formulas
- Four-game engine → Student learning model: reports performance
- Student learning model → Neural network: trains and predicts
- Student learning model → Profiles and settings: persists profile
- Moli controller → Moli OLED view: updates display
- Moli controller → Student learning model: requests diagnosis
- Moli controller → App controller: reads app context
- Student → Practice interface: plays games