praca_magisterska/scripts/test_scenarios.md

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Add comprehensive thesis completion game plan, tracking system, automation scripts, and publication-ready LaTeX chapter content with extensive citations (#4) * Initial plan * Add comprehensive thesis completion game plan (deadline Feb 10) Co-authored-by: kuhyx <147418882+kuhyx@users.noreply.github.com> * Add quick start guide and daily progress tracking template Co-authored-by: kuhyx <147418882+kuhyx@users.noreply.github.com> * Add visual tracker and planning system overview Co-authored-by: kuhyx <147418882+kuhyx@users.noreply.github.com> * Update work schedule to 4hrs weekdays, 8hrs weekends (144 total hrs) Co-authored-by: kuhyx <147418882+kuhyx@users.noreply.github.com> * Update dates to Jan 16-Feb 15, add helper scripts for data collection Co-authored-by: kuhyx <147418882+kuhyx@users.noreply.github.com> * Add complete LaTeX content for chapters 5-8, graph generation script, auto-compile script Co-authored-by: kuhyx <147418882+kuhyx@users.noreply.github.com> * Add extensive citations throughout chapters, fix Linux-specific issues, replace subjective language with objective data Co-authored-by: kuhyx <147418882+kuhyx@users.noreply.github.com> * Fix CI pipeline: use test_pdf instead of test target in workflow Co-authored-by: kuhyx <147418882+kuhyx@users.noreply.github.com> * Co-authored-by: kuhyx <147418882+kuhyx@users.noreply.github.com> --------- Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com> Co-authored-by: kuhyx <147418882+kuhyx@users.noreply.github.com>
2026-01-15 17:57:44 +01:00
# Test Scenarios Document
**Project**: Master's Thesis - Game Engine Performance Comparison
**Date**: January 16, 2026
**Author**: Krzysztof Rudnicki
---
## Overview
This document defines the test scenarios for comparing Unity and Unreal Engine performance using bullet-hell games and NVIDIA Nsight profiling.
---
## Test Hardware
*[Auto-generated by running: `./scripts/get_hardware_specs.sh`]*
- **CPU**: [Your CPU model]
- **GPU**: [Your GPU model]
- **RAM**: [Your RAM amount]
- **OS**: [Your OS version]
---
## Test Methodology
### Game: Bullet-Hell (Unity & Unreal implementations)
Both games implement identical gameplay mechanics:
- Player-controlled ship
- Enemy spawning system with escalating difficulty
- Bullet pattern generation
- Collision detection
- 90-second survival mode
### Performance Metrics to Capture
1. **Frame Time** (ms) - Time to render one frame
2. **FPS** (frames per second) - Derived from frame time
3. **GPU Utilization** (%) - Percentage of GPU capacity used
4. **Memory Usage** (MB) - VRAM and system RAM consumption
5. **Draw Calls** - Number of draw calls per frame
6. **Vertex Count** - Total vertices rendered per frame
---
## Test Scenarios
### Scenario 1: Low Difficulty (Baseline)
**Objective**: Establish baseline performance with minimal load
**Parameters**:
- **Bullet count on screen**: 50-100 bullets
- **Active enemies**: 2-3 enemies
- **Duration**: 30 seconds of gameplay
- **Captures**: 5 frame captures at different moments
**Expected Outcomes**:
- Stable frame rate (60 FPS target)
- Low GPU utilization (<50%)
- Minimal memory usage
**Nsight Capture Points**:
- 5 seconds into scenario
- 10 seconds into scenario
- 15 seconds into scenario
- 20 seconds into scenario
- 25 seconds into scenario
---
### Scenario 2: Medium Difficulty
**Objective**: Test performance under moderate load
**Parameters**:
- **Bullet count on screen**: 200-300 bullets
- **Active enemies**: 5-7 enemies
- **Duration**: 30 seconds of gameplay
- **Captures**: 5 frame captures at different moments
**Expected Outcomes**:
- Moderate GPU utilization (50-70%)
- Frame rate may drop slightly
- Increased memory usage
**Nsight Capture Points**:
- 5 seconds into scenario
- 10 seconds into scenario
- 15 seconds into scenario
- 20 seconds into scenario
- 25 seconds into scenario
---
### Scenario 3: High Difficulty (Stress Test)
**Objective**: Test performance under maximum load
**Parameters**:
- **Bullet count on screen**: 500+ bullets
- **Active enemies**: 10+ enemies
- **Duration**: 30 seconds of gameplay
- **Captures**: 5 frame captures at different moments
**Expected Outcomes**:
- High GPU utilization (>70%)
- Potential frame drops
- Maximum memory usage observed
**Nsight Capture Points**:
- 5 seconds into scenario (system stabilizing)
- 10 seconds into scenario (peak load)
- 15 seconds into scenario (sustained load)
- 20 seconds into scenario (peak load)
- 25 seconds into scenario (sustained load)
---
## Data Collection Procedure
### For Each Scenario:
1. **Pre-test Setup**:
- Close all background applications
- Disable system updates
- Set power mode to "High Performance"
- Wait 5 minutes for system stabilization
- Clear GPU/system caches
2. **Unity Testing**:
- Launch Unity bullet-hell game
- Navigate to scenario (Low/Medium/High)
- Start NVIDIA Nsight Graphics
- Attach Nsight to Unity process
- Play scenario for 30 seconds
- Capture frames at designated time points (5 captures)
- Save capture data with naming: `unity_[scenario]_capture_[N].nsight`
- Export metrics to CSV: `unity_[scenario]_metrics.csv`
3. **Unreal Testing**:
- Close Unity completely
- Wait 2 minutes for system cooldown
- Launch Unreal bullet-hell game
- Navigate to scenario (Low/Medium/High)
- Start NVIDIA Nsight Graphics
- Attach Nsight to Unreal process
- Play scenario for 30 seconds
- Capture frames at designated time points (5 captures)
- Save capture data with naming: `unreal_[scenario]_capture_[N].nsight`
- Export metrics to CSV: `unreal_[scenario]_metrics.csv`
4. **Post-test Data Organization**:
- Organize captures in folders: `data/nsight/unity/` and `data/nsight/unreal/`
- Compile metrics into master spreadsheet: `performance_comparison.xlsx`
- Take screenshots of key Nsight analysis views
- Document any anomalies or issues observed
---
## Expected Data Outputs
### Per Test Run (15 total: 3 scenarios × 5 captures):
- Nsight capture file (.nsight)
- Metrics CSV with frame time, FPS, GPU %, memory, draw calls, vertices
- Screenshot of Nsight GPU trace
- Screenshot of Nsight memory analysis
### Aggregate Data:
- Comparison table: Unity vs Unreal per scenario
- Performance graphs showing all metrics
- Statistical analysis (mean, std dev, min, max)
---
## Quality Assurance
### Validation Checks:
- [ ] All scenarios tested in both engines
- [ ] 5 captures per scenario completed
- [ ] All CSV metrics exported
- [ ] Screenshots saved for all captures
- [ ] Data organized in proper folder structure
- [ ] No system crashes or anomalies during testing
- [ ] Comparable conditions between Unity and Unreal runs
### Data Integrity:
- [ ] Frame times make sense (>0ms, <100ms typically)
- [ ] GPU utilization in valid range (0-100%)
- [ ] Memory values reasonable for game scope
- [ ] No obvious outliers without explanation
---
## Timeline
- **Day 1 (Thursday, Jan 16)**: Setup Nsight, run Scenario 1 on both engines
- **Day 2 (Friday, Jan 17)**: Run Scenario 2 on both engines
- **Day 3 (Saturday, Jan 18)**: Run Scenario 3 on both engines
- **Day 4 (Sunday, Jan 19)**: Verify data, re-run any problematic captures, organize data
---
## Notes
- If a capture fails, note the reason and retry
- Document any differences in how scenarios are triggered in Unity vs Unreal
- Pay attention to engine-specific optimizations that may affect results
- Consider recording video of test runs for reference
---
**Status**: Ready for execution
**Next Action**: Run `./scripts/get_hardware_specs.sh` to generate hardware specs for Chapter 4