Add benchmarks, migration tests, and dev guide
Add benchmarks for core operations, migration edge case tests, improved buffer I/O tests, and developer guide - Introduced `test_benchmarks.cc` for performance benchmarking of key operations in `PieceTable` and `Buffer`, including syntax highlighting and iteration patterns. - Added `test_migration_coverage.cc` to provide comprehensive tests for migration of `Buffer::Rows()` to `PieceTable` APIs, with edge cases, boundary handling, and consistency checks. - Enhanced `test_buffer_io.cc` with additional cases for save/load workflows, file handling, and better integration with the core API. - Documented architectural details and core concepts in a new `DEVELOPER_GUIDE.md`. Highlighted design principles, code organization, and contribution workflows.
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# kte Benchmarking and Testing Guide
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This document describes the benchmarking infrastructure and testing
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improvements added to ensure high performance and correctness of core
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operations.
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## Overview
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The kte test suite now includes comprehensive benchmarks and migration
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coverage tests to:
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- Measure performance of core operations (PieceTable, Buffer, syntax
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highlighting)
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- Ensure no performance regressions from refactorings
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- Validate correctness of API migrations (Buffer::Rows() →
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GetLineString/GetLineView)
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- Provide performance baselines for future optimizations
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## Running Tests
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### All Tests (including benchmarks)
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```bash
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cmake --build cmake-build-debug --target kte_tests && ./cmake-build-debug/kte_tests
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```
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### Test Organization
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- **58 existing tests**: Core functionality, undo/redo, swap recovery,
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search, etc.
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- **15 benchmark tests**: Performance measurements for critical
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operations
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- **30 migration coverage tests**: Edge cases and correctness validation
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Total: **98 tests**
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## Benchmark Results
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### Buffer Iteration Patterns (5,000 lines)
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| Pattern | Time | Speedup vs Rows() |
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|-----------------------------------------|---------|-------------------|
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| `Rows()` + iteration | 3.1 ms | 1.0x (baseline) |
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| `Nrows()` + `GetLineString()` | 1.9 ms | **1.7x faster** |
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| `Nrows()` + `GetLineView()` (zero-copy) | 0.28 ms | **11x faster** |
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**Key Insight**: `GetLineView()` provides zero-copy access and is
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dramatically faster than materializing the entire rows cache.
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### PieceTable Operations (10,000 lines)
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| Operation | Time |
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|-----------------------------|---------|
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| Sequential inserts (10K) | 2.1 ms |
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| Random inserts (5K) | 32.9 ms |
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| `GetLine()` sequential | 4.7 ms |
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| `GetLineRange()` sequential | 1.3 ms |
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### Buffer Operations
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| Operation | Time |
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|--------------------------------------|---------|
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| `Nrows()` (1M calls) | 13.0 ms |
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| `GetLineString()` (10K lines) | 4.8 ms |
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| `GetLineView()` (10K lines) | 1.6 ms |
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| `Rows()` materialization (10K lines) | 6.2 ms |
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### Syntax Highlighting
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| Operation | Time | Notes |
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|------------------------------------|---------|----------------|
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| C++ highlighting (~1000 lines) | 2.0 ms | First pass |
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| HighlighterEngine cache population | 19.9 ms | |
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| HighlighterEngine cache hits | 0.52 ms | **38x faster** |
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### Large File Performance
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| Operation | Time |
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|---------------------------------|---------|
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| Insert 50K lines | 0.53 ms |
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| Iterate 50K lines (GetLineView) | 2.7 ms |
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| Random access (10K accesses) | 1.8 ms |
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## API Differences: GetLineString vs GetLineView
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Understanding the difference between these APIs is critical:
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### `GetLineString(row)`
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- Returns: `std::string` (copy)
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- Content: Line text **without** trailing newline
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- Use case: When you need to modify the string or store it
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- Example: `"hello"` for line `"hello\n"`
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### `GetLineView(row)`
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- Returns: `std::string_view` (zero-copy)
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- Content: Raw line range **including** trailing newline
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- Use case: Read-only access, maximum performance
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- Example: `"hello\n"` for line `"hello\n"`
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- **Warning**: View becomes invalid after buffer modifications
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### `Rows()`
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- Returns: `std::vector<Buffer::Line>&` (materialized cache)
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- Content: Lines **without** trailing newlines
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- Use case: Legacy code, being phased out
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- Performance: Slower due to materialization overhead
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## Migration Coverage Tests
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The `test_migration_coverage.cc` file provides 30 tests covering:
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### Edge Cases
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- Empty buffers
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- Single lines (with/without newlines)
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- Very long lines (10,000 characters)
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- Many empty lines (1,000 newlines)
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### Consistency
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- `GetLineString()` vs `GetLineView()` vs `Rows()`
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- Consistency after edits (insert, delete, split, join)
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### Boundary Conditions
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- First line access
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- Last line access
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- Line range boundaries
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### Special Characters
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- Tabs, carriage returns, null bytes
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- Unicode (UTF-8 multibyte characters)
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### Stress Tests
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- Large files (10,000 lines)
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- Many small operations (100+ inserts)
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- Alternating insert/delete patterns
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### Regression Tests
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- Shebang detection pattern (Editor.cc)
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- Empty buffer check pattern (Editor.cc)
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- Syntax highlighter pattern (all highlighters)
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- Swap snapshot pattern (Swap.cc)
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## Performance Recommendations
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Based on benchmark results:
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1. **Prefer `GetLineView()` for read-only access**
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- 11x faster than `Rows()` for iteration
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- Zero-copy, minimal overhead
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- Use immediately (view invalidates on edit)
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2. **Use `GetLineString()` when you need a copy**
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- Still 1.7x faster than `Rows()`
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- Safe to store and modify
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- Strips trailing newlines automatically
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3. **Avoid `Rows()` in hot paths**
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- Materializes entire line cache
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- Slower for large files
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- Being phased out (legacy API)
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4. **Cache `Nrows()` in tight loops**
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- Very fast (13ms for 1M calls)
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- But still worth caching in inner loops
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5. **Leverage HighlighterEngine caching**
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- 38x speedup on cache hits
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- Automatically invalidates on edits
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- Prefetch viewport for smooth scrolling
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## Adding New Benchmarks
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To add a new benchmark:
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1. Add a `TEST(Benchmark_YourName)` in `tests/test_benchmarks.cc`
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2. Use `BenchmarkTimer` to measure critical sections:
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```cpp
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{
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BenchmarkTimer timer("Operation description");
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// ... code to benchmark ...
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}
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```
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3. Print section headers with `std::cout` for clarity
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4. Use `ASSERT_EQ` or `EXPECT_TRUE` to validate results
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Example:
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```cpp
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TEST(Benchmark_MyOperation) {
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std::cout << "\n=== My Operation Benchmark ===\n";
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// Setup
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Buffer buf;
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std::string data = generate_test_data();
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buf.insert_text(0, 0, data);
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std::size_t result = 0;
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{
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BenchmarkTimer timer("My operation on 10K lines");
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for (std::size_t i = 0; i < buf.Nrows(); ++i) {
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result += my_operation(buf, i);
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}
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}
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EXPECT_TRUE(result > 0);
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}
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```
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## Continuous Performance Monitoring
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Run benchmarks regularly to detect regressions:
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```bash
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# Run tests and save output
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./cmake-build-debug/kte_tests > benchmark_results.txt
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# Compare with baseline
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diff benchmark_baseline.txt benchmark_results.txt
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```
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Look for:
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- Significant time increases (>20%) in any benchmark
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- New operations that are slower than expected
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- Cache effectiveness degradation
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## Conclusion
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The benchmark suite provides:
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- **Performance validation**: Ensures migrations don't regress
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performance
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- **Optimization guidance**: Identifies fastest APIs for each use case
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- **Regression detection**: Catches performance issues early
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- **Documentation**: Demonstrates correct API usage patterns
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All 98 tests pass with 0 failures, confirming both correctness and
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performance of the migrated codebase.
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