November 17, 2025

Best Hackathon Project Ideas for Automation Testing [With Source Code]

What kind of project can truly stand out in a hackathon focused on testing, quality, and reliability? In automation-driven events, choosing the right idea matters even more because judges look for accuracy, speed, and smart workflows.

Automation projects shine when they reduce manual effort, detect errors early, or improve the overall quality of software systems. Exploring the right Automation Testing hackathon project ideas helps you create something practical, fast to build, and impressive during the final demo.

This guide brings simple and impactful automation ideas that you can quickly develop, test, and showcase with confidence in any hackathon.

Top Automation Testing Hackathon Projects – Overview

Here’s an overview of the 10 best Automation Testing hackathon project ideas:

S.No.	Project Title	Complexity	Estimated Time	Source Code
1	Automated Web Form Testing Suite	Easy	6–8 hours	Get Started
2	API Regression Test Automation Framework	Easy	7–10 hours	Get Started
3	Cross-Browser UI Testing Framework	Medium	10–12 hours	Get Started
4	Mobile App Test Automation for Android	Medium	12–14 hours	Get Started
5	Automated Performance and Load Testing Tool	Medium	12–16 hours	Get Started
6	Visual Regression Testing Tool	Medium	15–18 hours	Get Started
7	CI-based Automated Test Pipeline	Medium	18–22 hours	Get Started
8	Chatbot Testing Automation System	Hard	20–26 hours	Get Started
9	Smart Test Data Generator with AI	Hard	22–28 hours	Get Started
10	Intelligent Defect Prediction System	Hard	28–36 hours	Get Started

Key Focus Areas in Automation Testing Hackathons

Automation testing hackathons focus on building solutions that improve testing speed, accuracy, and overall software quality. Here are the key areas participants should prioritise:

Test Case Automation: Creating scripts that run repetitive test cases quickly and consistently.
API Testing Automation: Building tools to validate endpoints, responses, and integrations efficiently.
CI-based Testing: Ensuring automated tests run smoothly within continuous integration pipelines.
Performance and Load Testing: Checking system behaviour under different loads using automated scripts.
Bug Detection and Reporting: Identifying issues early and generating structured, actionable reports.
Cross Browser and Cross Device Testing: Validating UI behaviour across browsers, devices, and screen sizes.

10 Best Automation Testing Hackathon Project Ideas

Choosing the right idea is the first step to building a strong solution in any testing-focused event.

To help you get started, here are the best Automation Testing hackathon project ideas that are practical to build, easy to demonstrate, and valuable for real-world software quality needs.

1. Automated Web Form Testing Suite

A beginner-friendly tool that automatically tests form inputs, validations, and error messages across different browsers. It helps teams quickly catch common UI errors without repeated manual testing.

This project is ideal for hackathons because it is simple to build yet demonstrates clear value in real QA workflows.

Duration: 6–8 hours

Difficulty Level: Easy

Tech Stack Required: Selenium, Python, TestNG or PyTest

Implementation Steps:

Identify common form validations
Create reusable test scripts
Run tests across browsers
Generate a pass fail summary

Key Features:

Input field validation
Auto detection of UI errors
Multi browser execution

Learnings:

Selenium basics
Handling dynamic UI elements
Test framework organisation

Real-World Application:

Login forms
Signup and checkout pages

Get Started

2. API Regression Test Automation Framework

A simple but powerful framework that validates API responses, status codes, headers, and integration flows. It helps ensure backend stability whenever new releases happen. This project is great for showcasing clean automation structure and API first testing.

Duration: 7–10 hours

Difficulty Level: Easy

Tech Stack Required: Postman, Newman, JavaScript or Python

Implementation Steps:

Create API collections
Add test assertions
Set up environment variables
Automate execution with Newman

Key Features:

Automated API regression
Environment based testing
JSON schema validation

Learnings:

API testing
Writing assertions
Workflow automation

Real-World Application:

Microservices
Banking and fintech APIs

Get Started

3. Cross-Browser UI Testing Framework

A system that verifies if a website behaves consistently across Chrome, Firefox, Edge, and Safari. It highlights rendering issues, layout shifts, and broken UI components. It is ideal for hackathons because of its immediate visual impact and real-world use.

Duration: 10–12 hours

Difficulty Level: Medium

Tech Stack Required: Selenium Grid, WebDriver, Java or Python

Implementation Steps:

Set up Selenium Grid
Build page object tests
Run parallel sessions
Add HTML reporting

Key Features:

Multi browser compatibility
Parallel execution
Visual UI checks

Learnings:

Selenium Grid setup
Parallel test strategy
UI consistency validation

Real-World Application:

E commerce sites
Government portals

Get Started

4. Mobile App Test Automation for Android

A framework that automates testing of Android apps, including UI flows, gestures, and performance. It is perfect for teams wanting to explore mobile automation. It helps detect crashes, UI lag, and broken navigation early in the cycle.

Duration: 12–14 hours

Difficulty Level: Medium

Tech Stack Required: Appium, Java or Python, Android Studio

Implementation Steps:

Configure Appium server
Write test scripts
Automate gestures and flows
Add detailed reports

Key Features:

Click swipe automation
App install uninstall tests
Performance snapshots

Learnings:

Mobile test automation
Gestures and device actions
Debugging real devices

Real-World Application:

Fintech apps
E learning apps

Get Started

5. Automated Performance and Load Testing Tool

A tool that simulates hundreds of users to test the performance and stability of a website or API. It helps teams understand how the system behaves under pressure. This project makes a strong impression because performance testing is often ignored but extremely valuable.

Duration: 12–16 hours

Difficulty Level: Medium

Tech Stack Required: JMeter, Locust, Python

Implementation Steps:

Define load scenarios
Create scripts
Run stress and spike tests
Analyse test metrics

Key Features:

Response time tracking
Error rate measurement
Scalable load simulation

Learnings:

Load testing concepts
KPI based analysis
Bottleneck identification

Real-World Application:

High traffic portals
Online exam systems

Get Started

6. Visual Regression Testing Tool

A system that compares screenshots of UI pages between versions to catch layout changes, font issues, spacing errors, and unexpected UI shifts. It is impactful because visual bugs are common and often missed manually.

Duration: 15–18 hours

Difficulty Level: Medium

Tech Stack Required: Puppeteer, Cypress, ImageDiff libraries

Implementation Steps:

Capture baseline screenshots
Capture new build screenshots
Compare images
Highlight visual differences

Key Features:

Pixel by pixel comparison
Automated screenshot capture
Visual diff highlighting

Learnings:

Image comparison logic
Headless browser automation
UI snapshot testing

Real-World Application:

UI redesign testing
Branding compliance checks

Get Started

7. CI-based Automated Test Pipeline

A complete testing pipeline that runs automated tests on every code push and generates reports instantly. It ensures fast feedback to developers. This idea shows strong industry relevance because CI integration is a key part of modern testing.

Duration: 18–22 hours

Difficulty Level: Medium

Tech Stack Required: Jenkins or GitHub Actions, Selenium, API tests

Implementation Steps:

Set up CI workflow
Add test runners
Generate reports
Trigger builds from commits

Key Features:

Automated triggers
Real time feedback
Report storage

Learnings:

CI pipeline setup
Test scheduling
Report generation

Real-World Application:

DevOps automation
Enterprise testing

Get Started

8. Chatbot Testing Automation System

A tool that tests chatbot responses, intent detection accuracy, fallback messages, and integration flows. It is especially useful with modern conversational apps. The system ensures chatbots respond meaningfully and consistently across various scenarios.

Duration: 20–26 hours

Difficulty Level: Hard

Tech Stack Required: Python, Dialogflow API, Selenium

Implementation Steps:

Build conversation scenarios
Automate message sending
Validate response accuracy
Generate conversation reports

Key Features:

Intent validation
Response accuracy scoring
Scenario based testing

Learnings:

NLP bot testing
Functional scenario design
Response analysis

Real-World Application:

Customer support bots
In app assistants

Get Started

9. Smart Test Data Generator with AI

A generator that creates dynamic test data using AI based on schema rules, edge cases, and validation constraints. It reduces reliance on manual test data creation. This idea demonstrates innovation and strong relevance to testing productivity.

Duration: 22–28 hours

Difficulty Level: Hard

Tech Stack Required: Python, GPT APIs, Faker library

Implementation Steps:

Define data rules
Build generation engine
Add edge case support
Export data in CSV JSON

Key Features:

AI based data creation
Rule driven outputs
Edge case scenarios

Learnings:

Data modelling
Prompt based generation
Test scenario coverage

Real-World Application:

QA teams
Automation frameworks

Get Started

10. Intelligent Defect Prediction System

A machine learning tool that predicts potential failure points in code based on commit history, test results, and patterns. It helps teams reduce risk before releases. This is a high-impact idea suitable for experienced teams aiming to build analytical automation.

Duration: 28–36 hours

Difficulty Level: Hard

Tech Stack Required: Python, ML Models, Pandas, Streamlit

Implementation Steps:

Collect historical commit data
Train prediction model
Visualise failure risk
Show actionable insights

Key Features:

Failure risk scoring
Trend analysis
Developer level predictions

Learnings:

Predictive modelling
Data cleaning
Analytical dashboard design

Real-World Application:

Large codebases
Enterprise CI platforms

Get Started

Examples of Top Automation Testing Hackathon Winners

1. HyperHack 2022 – Test Automation Category: Team “Automata” won first place for creating a novel way to generate automated test workflows in the .xaml format using the UiPath Test Automation platform. The project significantly reduced the time needed to set up test cases.

2. ProvarLabs’ First Hackathon (2022) – Internal Test Automation Challenge: Team “Binary Souls” won by developing a live analytics engine that ingests logs across multiple systems and gives real-time observability into test execution. The winning idea exemplified automation of monitoring and insight rather than just functional test scripts.

3. Cignithon 2022 – Quality Assurance Hackathon: Team “Quality Advocates” (Rahul Parwal & Apoorva Ram) grabbed first place in the QA/automation stream, showcasing an end-to-end test automation solution for business applications. The competition emphasised QA and automation workflow innovation.

Final Words

Automation testing hackathons reward ideas that improve testing speed, accuracy, and overall software quality.

By choosing a focused problem, using the right tools, and building a clear workflow, you can create a solution that is both practical and impressive.

With the project ideas in this guide, you can prepare confidently and deliver a strong prototype within the hackathon time.

Frequently Asked Questions

1. What are the best Automation Testing project ideas for hackathons?

The best Automation Testing project ideas for hackathons include API regression frameworks, mobile automation, visual regression tools, CI based test pipelines, and intelligent defect prediction systems.

2. How do I choose the right Automation Testing project for a hackathon?

Choosing the right Automation Testing project for a hackathon depends on your team skills, available tools, time limits, and selecting a problem simple enough to automate quickly.

3. How can I make my Automation Testing hackathon project innovative?

Making your Automation Testing hackathon project innovative involves adding AI based insights, smart analytics, visual comparisons, auto healing tests, or deeper integrations with CI workflows for real testing value.

4. Where can I find open datasets for Automation Testing hackathon projects?

Open datasets for Automation Testing hackathon projects can be found on GitHub sample repos, Kaggle datasets, public API sandboxes, and mock server platforms that support automated testing.

5. Can beginners participate in Automation Testing hackathons?

Yes, beginners can participate in Automation Testing hackathons by choosing simple ideas like form automation or API testing and focusing on clean execution rather than complex frameworks.

6. What tools and frameworks are commonly used in Automation Testing projects?

Tools and frameworks used in Automation Testing projects include Selenium, Appium, Postman, Newman, JMeter, Cypress, Jenkins, and GitHub Actions for reliable and scalable test automation.

7. How can I complete an Automation Testing project quickly during a hackathon?

Completing an Automation Testing project quickly during a hackathon requires limiting scope, reusing libraries, using headless tests, preparing sample data early, and dividing tasks efficiently within the team.

Thirumoorthy

Thirumoorthy serves as a teacher and coach. He obtained a 99 percentile on the CAT. He cleared numerous IT jobs and public sector job interviews, but he still decided to pursue a career in education. He desires to elevate the underprivileged sections of society through education