Deep Dive into the RUXAILAB Codebase: Understanding Architecture for A/B Testing Integration

Source: Dev.to

Introduction

When I started exploring RUXAILAB, my goal was not just to understand how the platform works, but to figure out how a new system—A/B testing—could be integrated without disrupting its existing workflow. Instead of treating the repository as a collection of files, I approached it as a system, focusing on data flow, layer communication, and extensibility points.

System Overview

Study Lifecycle

1. A researcher creates a study.
2. Participants interact with the study interface.
3. Responses are stored in Firestore.
4. Analytics are generated based on collected data.

This flow is well‑structured and modular. RUXAILAB is not just a frontend‑heavy application; it is a coordinated system involving Vue modules, Firebase services, and backend logic.

Layered Architecture

• Frontend (Vue 3 + Vuex) – Handles UI, state management, and user interaction.
• Backend (Firebase) – Manages authentication, Firestore data, and Cloud Functions.
• Analysis Layer (Python) – Processes data for insights.

The clean separation of concerns makes the system highly extensible, allowing new functionality to be introduced as separate modules that integrate with these layers.

Integration Points for A/B Testing

1. Participant Entry – When a participant enters a study, assign them to a variant. This aligns with the existing router‑based flow, allowing logic injection without affecting UI components.
2. Data Collections – Extend existing collections (tests, answers, users) with an experiments collection. This lets experiment data coexist with current study data without breaking compatibility.
3. Event Logging – Leverage existing user interactions by logging events such as:
   • Task completion
   • Time on task
   • Error count

These events can serve as experiment metrics without redesigning the data model.

Core Realization

The best way to integrate A/B testing is not by changing the existing system, but by extending it. This aligns with the architectural goal of:

• Keeping the current workflow intact
• Introducing experimentation as a modular layer
• Reusing existing data pipelines

Practical Challenges Encountered

• Understanding how Vuex modules interact across features.
• Tracing Firestore data flow between frontend and backend.
• Identifying where business logic resides (frontend vs. Cloud Functions).

Approach to Overcome Challenges

• Followed data instead of files.
• Traced end‑to‑end flows rather than isolated components.
• Mapped interactions between frontend, backend, and database.

This method clarified not only what the code does, but why it is structured that way.

Prototype Implementation

Based on the study, I designed and implemented an A/B testing prototype that:

• Created a modular experiments feature
• Used Cloud Functions for deterministic assignment
• Designed a Firestore schema aligned with existing collections
• Integrated event logging into study interactions

The prototype fits naturally into RUXAILAB’s architecture, feeling like an internal addition rather than an external overlay.

Conclusion & Takeaways

Studying the RUXAILAB codebase provided a clear understanding of how a real‑world UX research platform is structured and how new features can be introduced without breaking existing systems. It helped me move from:

• Reading code → reasoning about systems
• Understanding features → designing integrations

This experience gave me confidence that I can implement an A/B testing framework that aligns with RUXAILAB’s architecture, maintains code quality, and supports future extensibility.