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Faadil Boussari's avatar
Faadil Boussari
proGatineau, Canada
Product Designer for AI & Digital Products
18
Followers
Product Designer for AI & Digital Products
Cover image for DAY 16: CONDITION TRACE 30 Days
DAY 16: CONDITION TRACE 30 Days of Real Business Problems Phase II I stopped at Day 15. Not because I ran out of problems. The format was becoming predictable. So I changed the rules. Phase II starts with a problem from museum conservation. Condition reports can document what was visible at different moments — but they cannot always prove when a physical change actually occurred. So instead of asking: “Where did the damage happen?” I reframed the problem: Trace when the feature first appears in the documentation. That became CONDITION TRACE. The prototype follows a fictional museum-loan case involving the same vessel across four signed condition records. Earlier examinations were completed under diffuse light. During the return-arrival inspection, the conservator introduces raking light. As the grazing angle changes, a hairline crack on the vessel’s upper-right shoulder becomes legible. That observation is preserved as OBS-04 and carried through a traceable evidence chain: SRC-03 → OBS-04 → CMP-01 → LIM-01 → FND-01 But the system deliberately refuses to overstate what the evidence proves. The earlier examinations were not performed under equivalent lighting conditions. So the conclusion remains narrow: FIRST DOCUMENTED APPEARANCE AUGUST 3, 2026 Not: “The damage happened on August 3.” Not cause. Not responsibility. Not liability. The interface follows the same principle. Light becomes an examination instrument. The observation persists through comparison. The evidence lineage remains visible. And the final finding must be deliberately sealed. The goal wasn’t to make an interface that looks forensic. It was to make the boundary of the evidence visible and traceable. TRACE THE RECORD. NOT THE BLAME. Live prototype: https://day16-condition-trace.vercel.app Day 16 / 30 Phase II begins.
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Cover image for CONDITION TRACE: Evidence in Motion
CONDITION TRACE: Evidence in Motion
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Cover image for A request does not automatically
A request does not automatically change an agreement. Scope Accord is a five-state interaction prototype designed around a common service-project problem: a client may hear “already included,” while the provider means “additional scope, cost and time.” The proposed change remains structurally outside the current agreement until both parties express the same understanding of its impact. One request. Two interpretations. One visible boundary. Designed and built with React, TypeScript, CSS Grid and Playwright. Live prototype: https://scope-accord.vercel.app
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Cover image for Day 9/30: VOLLENT A critical operational
Day 9/30: VOLLENT A critical operational change should not become executable just because every message was delivered. VOLLENT is an operational acknowledgment interlock that keeps execution physically open until every required recipient acknowledges the exact active version. In this scenario, a venue load-in changes from 2:00 PM to 3:00 PM. Three recipients have acknowledged it. Andre’s message was delivered but not acknowledged. So, the circuit stays open. Once Andre confirms the exact change: Delivery → acknowledgment → circuit closure → authorization → evidence receipt The signature interaction turns a missing acknowledgment into a physical gap. When the final recipient responds, the rails close, authorization becomes available and a version-bound receipt records the full sequence. SENT IS NOT SAFE. Delivery proves transmission. Acknowledgment releases execution. Built with React, Playwright, Remotion and FFmpeg. Communication channels are simulated in this working prototype, and the receipt tokens are deterministic demonstration artifacts rather than cryptographic proof. Live prototype: https://faadil1.github.io/vollent/ Full case study: https://contra.com/p/oc2QerNL-vollent-operational-acknowledgment-interlock?r=faadil_boussari #ProductDesign #InteractionDesign #UXDesign #Prototyping #FrontendDevelopment #MotionDesign Full case study: available on my Contra profile.
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Playwright(8)
Riadh 's avatar
Riadh
Tiaret, Algeria
Web Scraping & Automation, Data Extraction Expert
Web Scraping & Automation, Data Extraction Expert
Cover image for Local City Bus Lines Monitoring and Stops Identification
Local City Bus Lines Monitoring and Stops Identification
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10
Cover image for Pitch Venture Capital PortCos Data Collection
Pitch Venture Capital PortCos Data Collection
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3
Cover image for Twitch Community Detection & Lead Generation
Twitch Community Detection & Lead Generation
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9
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Mohsin Ishfaq's avatar
Mohsin Ishfaq
Lahore, Pakistan
Manual & Automation QA Engineer | Web, API & End-to-End Test
New to Contra
Manual & Automation QA Engineer | Web, API & End-to-End Test
Cover image for SauceDemo E2E Automation – Playwright
SauceDemo E2E Automation – Playwright Python + PyTest | POM Framework | 6 Tests Automated Overview: Automated https://www.saucedemo.com using Playwright Python + PyTest + Page Object Model built from scratch. Test Coverage (6 Tests): TC01 Valid login with standard_user TC03 Locked out user error validation TC09 Add single item to cart (Backpack) TC11 Remove item from products page TC15 Checkout with missing first name validation TC17 Complete happy path checkout E2E Framework: POM with login_page, products_page, cart_page, checkout_page, conftest fixtures, pytest-html reports, video recording Execution: 6/6 Passed | GitHub: https://github.com/mohsin-ishfaq/saucedemo-playwright-automation Tech: Python, Playwright Sync API, PyTest, POM
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Cover image for StockTargetAdvisor – Investment Research &
StockTargetAdvisor – Investment Research & Stock Analytics Platform QA [Canada] | FinTech | NDA Protected Overview: Canadian FinTech platform delivering stock ratings, target-price predictions, market insights, ML-powered investment recommendations. Work I Did: Tested financial data accuracy: stock ratings (Buy/Hold/Sell), target prices, research reports, watchlists, recommendation engine Validated dashboard calculations: portfolio performance, gain/loss, dividend yield Verified ML-generated insights match UI presentation across 20+ user workflows Regression testing each sprint - 70+ test cases Defect tracking in Trello - 30+ bugs reported Production verification post-deployment Tools: Manual Testing, Functional/Regression, Trello Domain: FinTech/Investment Research
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Cover image for NexaCare – Global Healthcare Second-Opinion
NexaCare – Global Healthcare Second-Opinion Platform QA | Global | NDA Protected Overview: HIPAA-compliant platform enabling patients, doctors, hospitals worldwide to get second opinions from board-certified US specialists. 4 roles: Patient, Doctor, Hospital, Specialist Panel. My Role: Manual QA Engineer Work I Did: Tested complete workflows for 4 distinct roles with different permissions Patient flow: Registration, case submission with medical records upload (DICOM, PDF, images), payment, specialist selection, communication, report receiving Doctor/Hospital flow: Patient referral, case tracking, record viewing, second opinion request Specialist Panel: Case assignment, review, report generation, secure messaging Validated medical record management: Upload validation (file type, size), secure storage, viewer functionality, download with watermark Security & Compliance: RBAC testing - verified Patient cannot see other patients, Doctor A cannot see Doctor B's patients, Hospital admin only sees own hospital cases. Tested HIPAA requirements - PHI encryption, audit logs, session timeout Functional/Regression/Smoke each release cycle - 100+ test cases executed Created detailed bug reports in Jira & Trello - 40+ bugs including 2 critical HIPAA RBAC issues Production verification before releases Impact: Ensured zero HIPAA violations in production, stable releases for global users Tools: Manual Testing, Jira, Trello, BrowserStack, Chrome DevTools Domain: Healthcare Global | Compliance: HIPAA
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Cover image for ConsidraCare – Healthcare & Home
ConsidraCare – Healthcare & Home Care Management Platform QA [Canada] | Sep 2024 – May 2025 | NDA Protected - Approach Only Project Overview: Canadian home-care platform enabling agencies to manage caregivers, clients, scheduling, care plans, payroll, invoicing. 4 portals: Client, Caregiver, Admin, Operations. My Role: QA Engineer (Manual + Automation + Security) Work I Did: Independently tested all 4 portals covering complex workflows: caregiver onboarding with background checks, shift scheduling with conflict detection, care plan management (ADLs), payroll calculations with overtime rules, invoicing with insurance integration Designed and executed 150+ test cases: Functional, Regression, Smoke, Cross-portal, End-to-End Built automated regression suite from scratch using Selenium Python + PyTest - 80 test cases automated, reduced regression time from 2 days to 4 hours API Testing: Validated 30+ REST APIs using Postman - caregiver availability, shift assignment, payroll generation, client billing - checked status codes, response schema, error handling, auth Database Testing: SQL verification - validated payroll calculations match DB, schedule conflicts prevented at DB level, invoice totals, data integrity across portals Security Testing: Foundational web security using Kali Linux tools - XSS in care notes, SQL Injection in search, authentication bypass, brute-force on login, role escalation checks HIPAA-adjacent validation: Ensured caregiver can only see assigned clients, client PHI masked for unauthorized roles, audit logs for sensitive actions Bug Reporting: Logged 60+ bugs in Jira with steps, expected/actual, severity, video proof for critical. Worked with devs through fix verification Release verification: Production smoke testing before each release, preventing critical payroll bugs Impact: Reduced production bugs by 40%, regression time by 75% Tools: Selenium Python, PyTest, Postman, MySQL, Jira, Kali Linux (Burp Suite, OWASP ZAP), BrowserStack, GitHub Domain: Healthcare | Type: Web Application | NDA: No confidential screenshots or data shared - approach only
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Playwright(4)
Sanket Sabharwal, PhD's avatar
Sanket Sabharwal, PhD
maxGenoa, Italy
Senior Software & ML Engineer | Zero to One Product Builder
6x
Hired
5.0
Rating
58
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Cover image for Web Scraping Systems - Large-Scale Data Extraction Pipelines
Web Scraping Systems - Large-Scale Data Extraction Pipelines
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Cover image for BI Dashboards - Retail Analytics & Forecasting
BI Dashboards - Retail Analytics & Forecasting
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Cover image for Computer Vision for Manufacturing - Defect Detection & QA
Computer Vision for Manufacturing - Defect Detection & QA
2
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Cover image for Machine Learning for Recommendation Systems - Personalization
Machine Learning for Recommendation Systems - Personalization
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31
Playwright(1)
Salman Khan's avatar
Salman Khan
Karachi, Pakistan
Webflow + AI Developer | Agents & Automation
5.0
Rating
35
Followers
Webflow + AI Developer | Agents & Automation
Cover image for Employee Management Automation System
Employee Management Automation System
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13
Cover image for TheMarcus.com – Webflow Portfolio Website
TheMarcus.com – Webflow Portfolio Website
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13
Cover image for Twice Bittn Bakery – E-Commerce Bakery Website
Twice Bittn Bakery – E-Commerce Bakery Website
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18
Cover image for VX Media Group – Global Agency Website
VX Media Group – Global Agency Website
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3
Playwright(1)