# QA Assessment: Executive Summary

**Date:** November 17, 2025
**Assessor:** QA/Test Engineer
**Roadmap:** 5 Priority Tasks (6 months)
**Overall Verdict:** FEASIBLE with strategic mitigations

______________________________________________________________________

## Key Findings at a Glance

### Task 2 (CMJ Testing 62%→80%): ACHIEVABLE

**Answer:** Yes, expanding to 80% coverage is feasible with structured test expansion.

```
Current:      62% CMJ coverage
Add ~40-50 new tests in 4 days:
├─ Phase progression:      +5-6%  (8-10 tests)
├─ Physiological bounds:   +4-5%  (12-15 tests)
├─ Real video validation:  +3-4%  (4-6 tests)
└─ Ankle fix validation:   +2-3%  (3-4 tests)
─────────────────────────────────
Target: 80%+ CMJ coverage ✓
```

**Success Criteria:** Phase angles increase 20°+ during concentric phase, all bounds validated, real video discriminates good/poor technique.

______________________________________________________________________

### Real-Time Testing (Task 3): CHALLENGING but MANAGEABLE

**Answer:** \<200ms latency target is achievable but requires early performance validation.

**Critical Path:**

- Week 1: Baseline latency profiling (single client)

  - If P50 \<150ms → Proceed ✓
  - If P50 >150ms → Investigate/optimize

- Week 2: Load testing (10, 25, 50 clients)

  - Goal: Maintain \<200ms P99 up to 50 concurrent users
  - Bottleneck: MediaPipe inference (likely 40-50ms)

- Fallback: Frame dropping + adaptive quality if needed

**Tools:** Apache JMeter, Locust, custom Python async testing

______________________________________________________________________

### Running Validation (Task 4): NO LAB EQUIPMENT NEEDED

**Answer:** Can validate without biomechanics lab using 3-tier approach.

```
Level 1: Published Research
├─ Compare GCT against biomechanics literature (0.35-0.50s for recreational)
├─ Cadence ranges 160-180 steps/min optimal
└─ Cost: Zero

Level 2: Consistency Testing
├─ Same video analyzed twice should give same metrics
├─ Metrics stable across camera angle variations
└─ Cost: Zero

Level 3: Crowdsourced Athlete Validation
├─ Recruit 10-20 runners with survey data
├─ Compare algorithm vs self-reported metrics
└─ Cost: Minimal (no equipment needed)

Result: Sufficient for MVP validation ✓
```

______________________________________________________________________

### Regression Prevention for 3-Sport Platform: STRUCTURED APPROACH

**Critical Regression Tests:**

| Test Category                              | Priority | Effort  | Coverage |
| ------------------------------------------ | -------- | ------- | -------- |
| Metric regression (baseline comparison)    | HIGH     | 1 day   | 3-4%     |
| Phase detection across sports              | HIGH     | 2 days  | 5-6%     |
| Biomechanics validation (triple extension) | HIGH     | 1 day   | 2-3%     |
| API consistency across sports              | MEDIUM   | 1 day   | 2%       |
| CLI commands all sports                    | MEDIUM   | 1 day   | 2%       |
| Batch processing regression                | MEDIUM   | 0.5 day | 1%       |

**Total New Regression Tests:** 50-60 tests, ~5-6 days effort

______________________________________________________________________

### Integration Testing for APIs: STANDARD APPROACH

**Test Coverage:**

```
API Endpoints:
├─ Create analysis (POST)
├─ Get results (GET)
├─ List analyses (GET)
├─ Rate limiting (429 response)
└─ Authentication (401/403 responses)

Webhooks:
├─ Fire on completion
├─ Payload contains correct metrics
├─ Retry on failure with backoff
└─ Ordering guarantee

Multi-User:
├─ Data isolation (User A can't see User B)
├─ Concurrent requests (50 users)
├─ Team aggregation (6 athletes → team summary)
└─ Session management (token expiration)
```

**Test Infrastructure:** FastAPI TestClient + mock webhook receiver

______________________________________________________________________

### Performance Benchmarks: LATENCY-FOCUSED

**Real-Time Latency Budget (\<200ms E2E):**

```
Capture:        33ms (30fps)
Network:        50ms (WebSocket roundtrip)
Processing:     50ms (MediaPipe bottleneck)
Rendering:      33ms (browser paint)
──────────────────
Total:         166ms (within budget) ✓
```

**Load Test Scenarios:**

| Clients | P50     | P95     | P99     | Status     |
| ------- | ------- | ------- | ------- | ---------- |
| 1       | \<100ms | \<150ms | \<200ms | Must pass  |
| 10      | \<120ms | \<170ms | \<200ms | Must pass  |
| 50      | \<140ms | \<190ms | \<200ms | Must pass  |
| 100     | TBD     | TBD     | >200ms  | Find limit |

______________________________________________________________________

## Risk Assessment Summary

### 🔴 CRITICAL RISKS (High Impact × High Likelihood)

| Risk                     | Likelihood | Impact    | Mitigation                        |
| ------------------------ | ---------- | --------- | --------------------------------- |
| Real-time latency >200ms | MEDIUM     | VERY HIGH | Week 1 profiling + early decision |
| Ankle fix breaks tests   | LOW        | VERY HIGH | Comprehensive pre/post validation |

**Mitigation Strategy:** Establish performance baseline immediately (Week 1), don't proceed with optimization after seeing baseline.

### 🟡 MEDIUM RISKS (High Impact × Medium Likelihood)

| Risk                                        | Likelihood | Impact | Mitigation                  |
| ------------------------------------------- | ---------- | ------ | --------------------------- |
| Multi-sport architecture generalizes poorly | MEDIUM     | HIGH   | Architecture review Week 2  |
| Task 2 coverage doesn't hit 80%             | MEDIUM     | MEDIUM | Daily coverage tracking     |
| WebSocket reliability under load            | MEDIUM     | MEDIUM | Chaos testing + retry logic |

**Mitigation Strategy:** Validate abstraction before implementing Task 4. Track coverage daily.

______________________________________________________________________

## Resource Requirements

**Total: 4-5 developers for 6 weeks**

| Role                     | Allocation | Tasks                                  |
| ------------------------ | ---------- | -------------------------------------- |
| QA Engineer              | 100%       | Task 2, regression tests, load testing |
| Backend Developer        | 60%        | All tasks (infrastructure support)     |
| Biomechanics Specialist  | 30%        | Task 1, 2, 4 validation                |
| Computer Vision Engineer | 40%        | Task 3 (real-time)                     |
| Technical Writer         | 30%        | Task 5 (API docs)                      |

______________________________________________________________________

## Critical Success Factors

**Week 1 Must-Haves:**

- [ ] Real-time latency baseline: P50 \<150ms measured
- [ ] Ankle angle fix: Comprehensive test suite prepared
- [ ] Test infrastructure: Baseline metrics snapshots taken

**Go/No-Go Decision Points:**

- **Week 1:** Real-time latency \<150ms P50 → GO
- **Week 2:** CMJ coverage trending 75%+ → GO
- **Week 4:** Running architecture tests pass → GO

______________________________________________________________________

## Recommendations

### Immediate Actions

1. **Establish Performance Baseline (3 days)**

   - Profile single-client real-time latency
   - Identify MediaPipe bottleneck
   - Set realistic targets

1. **Prepare Task 1 Validation (2 days)**

   - Finalize foot_index test suite
   - Get biomechanics specialist review
   - Plan rapid rollback if needed

1. **Finalize Task 2 Scope (1 day)**

   - Confirm 40-50 new tests feasible
   - Reserve resources for test implementation

### Testing Infrastructure Investment

**Setup Required (3-4 days):**

- Synthetic video generation framework
- WebSocket load testing harness
- Latency profiling infrastructure
- Regression test baseline snapshots
- CI/CD performance gates

**Expected ROI:**

- Catch regressions automatically
- Prevent performance degradation
- Enable confident deployment

______________________________________________________________________

## Bottom Line

✓ **The roadmap is achievable** with current test infrastructure as foundation.

✓ **Task 2 coverage expansion to 80%** is feasible with 40-50 new tests.

✓ **Real-time \<200ms latency** is likely achievable but needs early validation (Week 1).

✓ **Running validation without lab** is practical using published research + consistency testing.

✓ **Multi-sport platform** extensible if phase detection abstraction properly designed (Week 2 validation).

⚠️ **Key risks** are performance-related—early profiling is critical.

✓ **Confidence level: HIGH** (existing 74% coverage provides solid foundation)

______________________________________________________________________

**Next Step:** Schedule Week 1 latency baseline testing and ankle fix validation preparation.

**Full Assessment:** See QA_ROADMAP_ASSESSMENT.md (comprehensive technical details)

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**Assessment Date:** November 17, 2025
**Valid Through:** December 17, 2025 (reassess if scope changes)
