01
Requirement analysis
Study the Requirement Analysis Document, clarify ambiguity, identify risk areas, and turn requirements into test scenarios, cases, and traceability coverage.
QA
QA engineering that makes release risk visible.
I design test coverage, catch release risks, and document defects developers can act on. For hiring managers who need a QA engineer who can plan, execute, automate, and explain the state of quality before a release.
QA position
I do not just click through screens. I turn requirements into release evidence: RTMs, cases, execution records, defects, automation, and performance reports.
- Renuir test cases
- 173
- Salesgroup cases
- 75+
- Concurrent users
- 500+
Written from the Requirement Analysis Document with scenarios and RTM analysis.
Launch-readiness coverage across core SaaS workflows.
JMeter load tests used to expose backend bottlenecks.
QA story
The work is coverage, clarity, and confidence.
At Renuir, I work as the Test Engineer. I used the Requirement Analysis Document to write test scenarios, 173 test cases, and RTM analysis across 20+ feature modules, helping the team see what was ready, what was blocked, and what still needed attention before launch.
At RaftMedia, I led QA for Salesgroup.ai with 75+ launch-readiness test cases, JMeter performance tests from 100 to 500 concurrent users, API validation with Postman and Rest Assured, and continuous testing through Jenkins and GitHub Actions.
In healthcare AI work, I tested more than UI behavior: CORS, auth flows, serialization, E2E journeys, AI response quality, relevance, safety, and release smoke coverage across web and mobile.
Process
How I move from requirements to sign-off.
02
RTM and coverage design
Map each requirement to scenarios and test cases so coverage gaps are visible before release pressure begins.
03
Test case design
Write preconditions, data, steps, expected results, priority, and platform coverage using BVA, ECP, decision tables, and negative paths.
04
Execution and evidence
Run smoke, functional, E2E, regression, API, and mobile tests while capturing reproducible evidence for every failure.
05
Automation and performance
Use Playwright, Postman, Rest Assured, Apache JMeter, Jenkins, and GitHub Actions where automation gives faster release feedback.
06
Defect lifecycle
Report severity, priority, actual vs expected behavior, root-cause notes, retest results, and closure evidence.
Techniques
Test design is where QA earns its keep.
The reference page showed this well: smart QA explains why a few carefully chosen cases can cover a large risk surface.
BVA / ECP widget
Smart coverage, fewer cases.
Example: an age field accepts values from 18 to 56. I do not test every number. I partition the input space and focus on the boundaries where off-by-one bugs usually appear.
Invalid
< 18, e.g. 17
Valid
18 to 56
Invalid
> 56, e.g. 57
Classify a value to see how the input space is tested.
Live demo
Run the suite and watch one defect become a report.
This is a small demo, but the artifact shape is real: test ID, expected vs actual, severity, priority, environment, and reproduction steps.
demo-store.test/login
Mock app
Sign in
Valid login: ayodele@test.com / Test@123. The empty-field case intentionally fails so the bug report appears.
Run a failing negative case to generate the defect report.
Test suite
Login module
- Executed
- 0
- Passed
- 0
- Failed
- 0
Toolkit
Manual depth with automation and performance range.
Manual QA
- Test plans
- Test cases
- RTM
- Smoke
- Regression
- UAT
- Mobile QA
Automation
- Playwright
- Rest Assured
- Postman
- GitHub Actions
- Jenkins
Performance
- Apache JMeter
- 100-500 user load
- JTL analysis
- Bottleneck reports
Domains
- AI SaaS
- Healthcare AI
- Mobile launch
- API contracts
- Cross-browser testing
QA case studies
