Add comprehensive additional benchmark metrics section
- Added System Resources section (CPU, Memory, I/O metrics) - Added Performance Metrics section (Startup, Compilation, Binary Size) - Added Quality Metrics section (Code Quality, Security, Portability) - Added Developer Experience section (IDE, Community, Documentation) - Added Cost Analysis section (Development, Runtime costs) - Added Scalability section (Performance, Data scaling) - Added Language-Specific Metrics section - Added Measurement Tools section (Linux, macOS, Universal) - Added Recommended Additions section - Added Example Measurements section This provides a comprehensive overview of additional metrics that could be valuable when benchmarking programming languages beyond just execution time and memory usage.
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Ein Anderssono
@@ -642,6 +642,221 @@ The benchmark includes a detailed profiling system that breaks down execution ti
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See [PROFILING.md](PROFILING.md) for detailed documentation.
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## Additional Benchmark Metrics
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Beyond execution time and memory usage, there are many other metrics that can be valuable when benchmarking programming languages:
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### System Resources
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#### CPU Metrics
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- **CPU Instructions**: Number of instructions executed
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- **CPU Cycles**: Clock cycles per instruction (CPI)
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- **Cache Misses**: L1, L2, L3 cache misses
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- **Branch Prediction**: Missed branch predictions
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- **CPU Cores**: Number of cores utilized
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#### Memory Metrics
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- **Virtual Memory**: Total allocated memory
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- **Memory Fragmentation**: Wasted memory due to fragmentation
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- **Memory Leaks**: Memory not properly freed
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- **Memory Patterns**: Allocation patterns over time
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- **Stack vs Heap**: Stack vs heap memory usage
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#### I/O Operations
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- **Disk Reads**: Bytes read from disk
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- **Disk Writes**: Bytes written to disk
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- **Network I/O**: Bytes sent/received
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- **File Handles**: Number of open files
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### Performance Metrics
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#### Startup Time
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- **Cold Start**: Time to start program first time
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- **Warm Start**: Time to start program after cache
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- **JIT Warmup**: Time for JIT to optimize code
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#### Compilation Time
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- **Compilation**: Time to compile source code
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- **Linking**: Time to link binary
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- **Optimization**: Time for compiler optimizations
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#### Binary Size
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- **Binary Size**: Size of compiled binary
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- **Stripped Binary**: Size after stripping debug info
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- **Debug Info**: Size with debug information
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### Quality Metrics
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#### Code Quality
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- **Lines of Code (LOC)**: Code lines
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- **Cyclomatic Complexity**: Code complexity
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- **Maintainability Index**: Maintainability
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- **Technical Debt**: Technical debt
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#### Security
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- **Memory Safety**: Buffer overflows, use-after-free
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- **Type Safety**: Type errors at compile/runtime
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- **Vulnerabilities**: Known security holes
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#### Portability
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- **Platforms**: Supported platforms
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- **Architectures**: x86, ARM, etc.
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- **Operating Systems**: Windows, Linux, macOS
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### Developer Experience
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#### Development Environment
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- **IDE Support**: Syntax highlighting, autocomplete
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- **Debugging**: Step-by-step debugging
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- **Profiling**: Performance profiling
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- **Documentation**: Quality of documentation
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#### Community & Ecosystem
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- **Libraries**: Available libraries
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- **Package Managers**: npm, pip, cargo, etc.
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- **Community Size**: Number of developers
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- **Stack Overflow**: Questions/answers
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### Cost Analysis
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#### Development Cost
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- **Learning Curve**: Time to learn language
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- **Productivity**: Code per time unit
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- **Debugging**: Time to find/fix bugs
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- **Maintenance**: Time to maintain code
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#### Runtime Cost
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- **Server Cost**: CPU, memory, disk
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- **Energy Cost**: Power consumption
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- **Licenses**: Cost for tools/libraries
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### Scalability
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#### Performance Scaling
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- **Vertical Scaling**: Performance with more CPU/memory
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- **Horizontal Scaling**: Performance with more instances
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- **Concurrency**: Performance impact of parallelism
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#### Data Scaling
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- **Data Size**: Performance with more data
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- **Complexity**: Time complexity (O(n), O(n²), etc.)
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- **Memory Complexity**: Memory complexity
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### Language-Specific Metrics
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#### Compiled Languages
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- **Compilation Time**: Time to compile
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- **Binary Size**: Size of binary
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- **Optimization Levels**: -O0, -O1, -O2, -O3
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- **Linking Time**: Time to link
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#### JIT Languages
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- **JIT Warmup**: Time for JIT to optimize
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- **Deoptimization**: When JIT falls back
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- **GC Pauses**: Garbage collection pauses
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- **HotSpot Optimization**: JIT optimizations
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#### Interpreted Languages
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- **Interpretation Overhead**: Overhead for interpretation
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- **Bytecode Size**: Size of bytecode
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- **Dynamic Typing**: Overhead for type checking
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- **Eval Performance**: Performance of dynamic code
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### Measurement Tools
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#### Linux
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```bash
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# CPU performance
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perf stat -e cache-misses,cache-references ./program
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# Memory usage
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/usr/bin/time -v ./program 2>&1 | grep "Maximum resident"
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# Page faults
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/usr/bin/time -v ./program 2>&1 | grep "page faults"
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```
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#### macOS
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```bash
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# CPU and memory
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/usr/bin/time -l ./program
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# Binary size
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ls -lh program
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strip program
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ls -lh program
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# Compilation time
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time gcc -O2 program.c -o program
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```
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#### Universal
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```bash
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# Basic timing
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time ./program
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# Benchmarking
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hyperfine --warmup 3 './program'
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# Memory profiling
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valgrind --tool=massif ./program
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```
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### Recommended Additions
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#### New Metrics to Add
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1. **Binary Size** for all languages
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2. **Compilation Time** for compiled languages
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3. **Startup Time** (cold vs warm)
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4. **CPU Instructions** (if possible)
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5. **Cache Misses** (if possible)
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6. **Page Faults** (if possible)
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7. **Energy Consumption** (if possible)
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#### New Charts to Create
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1. **Binary Size vs Performance**
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2. **Compilation Time vs Performance**
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3. **Memory Usage Over Time**
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4. **CPU Usage Over Time**
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5. **Performance Scaling with Decimals**
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### Example Measurements
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#### Binary Size Comparison
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```
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Language Binary Size (KB) Stripped (KB)
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Assembly 16 12
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C 824 612
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C++ 1,024 768
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Rust 1,536 1,024
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Go 2,048 1,536
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Java N/A (JVM) N/A
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Python N/A (interpreted) N/A
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```
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#### Compilation Time
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```
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Language Compilation Time (ms)
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C 50
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C++ 75
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Rust 200
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Go 150
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Java 100
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```
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#### Startup Time
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```
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Language Cold Start (ms) Warm Start (ms)
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C 1 1
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Java 150 50
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Python 30 10
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Node.js 100 30
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```
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---
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**Note**: This benchmark currently measures execution time and memory usage. Adding these additional metrics would provide a more comprehensive view of language performance, but would require additional tooling and measurement infrastructure.
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## License
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MIT License - See LICENSE file for details.
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