QA Portfolio Projects to Showcase on GitHub

Overview

A QA portfolio should show decisions, not merely test files. Reviewers want to see how you identified risk, chose coverage layers, structured evidence, diagnosed failures, and made the project usable for another engineer. A repository containing 200 generated scripts with no explanation is much weaker than a focused project with 20 purposeful tests and a clear account of engineering tradeoffs.

You do not need ten repositories. Two polished projects can demonstrate more range than a crowded profile of abandoned tutorials. The ideas in this guide cover browser automation, APIs, exploratory testing, accessibility, mobile, performance, and CI. Each can be scaled to your experience level and built against an open-source application, a public demo system, or a small application you own.

Design the Portfolio Around Evidence

Start with the capability you need to prove. If target roles require Playwright and API testing, one project can combine API-created test data with browser validation. If you are moving from manual testing, a risk assessment, exploratory charters, defect reports, and a small regression suite may tell a stronger story. The repository should answer a hiring question, not exist only because a course assigned it. Write a one-sentence project promise before coding: "This project demonstrates reliable testing of a reservation workflow across API and UI layers, including concurrency and timezone risks." That statement disciplines scope. It also helps you decide what not to include. A weather app login test adds little if the project's promised evidence is payment resilience.

• Target role and capability the project proves
• System and business risk under test
• Coverage layers and why each was chosen
• Observable result, report, or investigation artifact
• Known limits and realistic next steps

Project One: Risk-Based E-Commerce Automation

Build an end-to-end project around a small set of commerce risks: price changes, inventory, cart persistence, discount rules, checkout validation, and order confirmation. Use Playwright, Cypress, or Selenium, but keep the framework proportional. Demonstrate stable locators, isolated data, reusable domain actions, and deliberate browser coverage. Add API setup if the application provides suitable endpoints. Do not automate every visible page. Include a risk matrix showing why checkout receives deeper coverage than footer links. Add tags for smoke and regression execution, plus one example of trace or screenshot diagnostics. A short note explaining why you avoided testing third-party payment internals shows better judgment than pretending a sandbox iframe proves the entire payment network.

• Critical paths: product selection, pricing, checkout, confirmation
• Failure paths: invalid coupon, stock change, expired session, rejected payment
• Engineering evidence: fixtures, test data, retries policy, CI artifacts
• Discussion point: which checks belong at API or component level instead

Project Two: API Contract and Data Integrity Suite

Choose a documented public API or run an open-source service locally. Validate more than status codes: response schemas, state changes, authorization, invalid payloads, duplicate requests, pagination, and database effects when accessible. Organize tests around resources and behavior rather than one file per HTTP method. Include safe environment configuration and never commit tokens. For additional depth, create a small consumer that depends on selected response fields and add contract validation. Document the difference between the OpenAPI schema check and the consumer expectation. If the API emits events, follow one transaction through an event or read model. Reviewers should see that an accepted request is not always the end of the test.

• Positive, boundary, negative, and permission scenarios
• Schema or contract validation with readable failure output
• Test data creation, cleanup, and parallel isolation
• Response-to-database or event consistency checks
• CI command that returns a reliable pass or fail result

Project Three: Exploratory Testing Case Study

A manual testing portfolio can be technical and rigorous. Select a real open-source or public application and create a short product map, risk analysis, and several time-boxed exploratory charters. Record observations, variations attempted, questions raised, and defects found. Protect user data and follow the site's acceptable-use rules. Do not aggressively test a production system without permission. Publish two or three excellent defect reports rather than a spreadsheet with dozens of superficial issues. Each report should include a concise title, environment, setup, numbered steps, actual and expected behavior, impact, and visual or log evidence. Add a session summary explaining what changed in your understanding and what you would investigate next. This exposes reasoning that a test-case count cannot.

• Charter: Explore password reset interruptions and repeated submissions to identify account lockout or disclosure risks.
• Charter: Vary locale, timezone, and daylight-saving boundaries across recurring appointment creation.
• Charter: Interrupt file uploads through refresh, duplicate selection, unsupported types, and poor connectivity.
• Artifact: One-page coverage map linking risks, observations, and remaining questions.

Project Four: Accessibility Quality Review

An accessibility project should combine automated checks with manual evaluation. Run an accessibility engine for fast detection, then test keyboard operation, focus order, visible focus, accessible names, headings, zoom, form errors, and screen-reader announcements where you have the skill. State the relevant WCAG version and success criteria accurately rather than declaring an entire site compliant. Choose one workflow, such as account creation or ticket purchase, and describe how each issue affects a user. A report saying "button fails 4.1.2" is less useful than an explanation that a screen-reader user hears "button" without the action name. Include recommended fixes, retest evidence, and limitations of your review. That combination demonstrates care and technical clarity.

• Automated scan results with false positives reviewed
• Keyboard and focus sequence recording
• Issue mapping to applicable success criteria
• User impact, suggested remediation, and retest status
• Clear statement that a focused review is not a compliance certification

Project Five: Mobile Test Strategy and Automation

For mobile roles, build around platform behavior instead of copying web test cases into Appium. Test permission changes, background and foreground transitions, interruptions, orientation, deep links, offline behavior, OS versions, and device constraints. A small native sample app or an open-source application is safer and easier to reproduce than an uncontrolled production target. Document a practical device matrix. Explain why you selected one recent Android emulator, one older supported version, and perhaps an iOS simulator. Add only a few automated journeys, then show manual charters for behaviors that are expensive or unreliable to automate. This balance signals that you choose tools according to feedback value.

• Automated smoke path using Appium with stable accessibility identifiers
• Offline draft creation followed by reconnection and synchronization
• Permission denial, later grant, and settings-level revocation
• Incoming call or background interruption during a multi-step form
• Device matrix tied to supported users rather than random availability

Project Six: Performance Investigation

A credible performance project defines a workload before running a tool. Model a scenario such as product search, report generation, or bulk record creation. Set a modest objective, build representative data, run a baseline, and inspect latency distribution, throughput, errors, and resource evidence that the system exposes. Avoid claiming production capacity from a laptop test against a public demo. The most interesting artifact is often the analysis. Explain why p95 matters, what changed as concurrency increased, and which evidence supports a bottleneck hypothesis. If you can modify a local system, make one improvement and compare results using the same conditions. Record limitations such as network variability, warm caches, and small data volume. Honest limits strengthen the project.

• k6 or JMeter script with versioned workload configuration
• Baseline and comparison run with reproducible conditions
• Latency percentiles, error rate, throughput, and server observations
• A reasoned bottleneck hypothesis rather than an unsupported verdict

Make Every Repository Reviewer-Friendly

A reviewer should understand the project within two minutes. The README needs the problem, tested risks, architecture, prerequisites, setup, commands, reports, and limitations. Use a diagram only when it clarifies test layers or data flow. Add a sample environment file with placeholders, lock dependency versions, and verify the instructions from a clean clone. Repository hygiene is part of the evidence. Use meaningful commits, a focused directory structure, linting, and a license appropriate to your code and dependencies. Exclude generated reports when they create noise, but publish a small sample through artifacts or a static page. Never include employer code, customer data, copied course solutions, or secrets.

• README starts with the quality problem, not installation details.
• One command runs the primary test path locally.
• CI status is current and failures expose useful diagnostics.
• Dependencies, test accounts, and cleanup behavior are documented.
• Known gaps show judgment and create interview discussion.

Present the Portfolio on Your Resume

List the portfolio as one or two projects with achievement-style bullets. Instead of "Created automation framework using Playwright," write "Designed Playwright coverage for checkout pricing and inventory risks using API-seeded data, parallel-safe fixtures, and GitHub Actions." A second bullet can mention negative paths, diagnostics, or documented tradeoffs. Do not attach invented business results to a demonstration project. Link to the specific repository, not only your GitHub profile. Use a clean URL and test it from a signed-out browser. In interviews, be ready to share your screen and explain one test, one design decision, one defect, and one improvement you would make next. A modest project you understand completely is safer than an elaborate project assembled from copied code.

Frequently Asked Questions

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