Défi Deck Dropout

What We Built

Deck Dropout is an automation tool designed to simulate realistic user behavior in order to navigate and complete multi-step web workflows smoothly.
The project focuses on reliability, stealth, and user control rather than brute-force automation.

At a high level, our system:

Automates navigation through complex web interfaces
Detects and interacts with dynamic UI elements (buttons, dropdowns, forms)
Mimics human behavior to avoid bot detection
Ensures that each step is validated before moving forward

How We Built It

Our architecture is built around browser automation and event-based control:

Python + Selenium (undetected_chromedriver) to control the browser
Explicit waits and XPath selectors to ensure stability with dynamic DOM elements
Human-like interaction patterns (mouse movement, scrolling, delays)
A modular design separating:
- navigation logic
- UI element detection
- user interaction simulation

We paid special attention to XPath precision to avoid ambiguity between similar elements, ensuring that each interaction targets the correct component even in crowded interfaces.

Challenges We Faced

One of the biggest challenges was bot detection.
Many platforms actively detect automation through:

lack of mouse movement
unrealistically fast interactions
static timing patterns

To overcome this, we implemented:

randomized delays
continuous mouse motion
scrolling-based visibility checks before interaction

Another challenge was dealing with dynamic pop-ups and modals, where elements exist in the DOM but are not interactable until scrolled into view. This required careful synchronization between scrolling, visibility checks, and clicks.

What We Learned

Through this project, we learned:

How fragile automation can be without proper synchronization
The importance of mimicking real user behavior rather than optimizing for speed
How to design automation systems that are robust, modular, and adaptable
How front-end design decisions directly impact automation complexity

Most importantly, we learned how to collaborate efficiently under time pressure and make pragmatic engineering choices to deliver a functional prototype within the hackathon timeframe.