11 Commits

13 changed files with 49600 additions and 61 deletions

3
.gitmodules vendored
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@@ -1,3 +0,0 @@
[submodule "tests/lib/catch2"]
path = tests/lib/catch2
url = https://github.com/catchorg/Catch2.git

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@@ -7,10 +7,10 @@
#include <sstream>
#include <fstream>
#include <cctype> // std::isdigit
#include <algorithm> // std::all_of
#include <algorithm> // std::all_of std::transform
class ArffFiles {
const std::string VERSION = "1.0.0";
const std::string VERSION = "1.1.0";
public:
ArffFiles() = default;
void load(const std::string& fileName, bool classLast = true)
@@ -28,8 +28,9 @@ public:
attributes.erase(attributes.begin());
labelIndex = 0;
}
preprocessDataset(labelIndex);
generateDataset(labelIndex);
};
}
void load(const std::string& fileName, const std::string& name)
{
int labelIndex;
@@ -48,27 +49,67 @@ public:
if (!found) {
throw std::invalid_argument("Class name not found");
}
preprocessDataset(labelIndex);
generateDataset(labelIndex);
};
std::vector<std::string> getLines() const { return lines; };
unsigned long int getSize() const { return lines.size(); };
std::string getClassName() const { return className; };
std::string getClassType() const { return classType; };
std::vector<std::string> getLabels() const { return labels; }
}
std::vector<std::string> getLines() const { return lines; }
unsigned long int getSize() const { return lines.size(); }
std::string getClassName() const { return className; }
std::string getClassType() const { return classType; }
std::map<std::string, std::vector<std::string>> getStates() const { return states; }
std::vector<std::string> getLabels() const { return states.at(className); }
static std::string trim(const std::string& source)
{
std::string s(source);
s.erase(0, s.find_first_not_of(" '\n\r\t"));
s.erase(s.find_last_not_of(" '\n\r\t") + 1);
return s;
};
std::vector<std::vector<float>>& getX() { return X; };
}
std::vector<std::vector<float>>& getX() { return X; }
std::vector<int>& getY() { return y; }
std::map<std::string, bool> getNumericAttributes() const { return numeric_features; }
std::vector<std::pair<std::string, std::string>> getAttributes() const { return attributes; };
std::vector<int> factorize(const std::vector<std::string>& labels_t)
std::vector<std::string> split(const std::string& text, char delimiter)
{
std::vector<std::string> result;
std::stringstream ss(text);
std::string token;
while (std::getline(ss, token, delimiter)) {
result.push_back(trim(token));
}
return result;
}
std::string version() const { return VERSION; }
protected:
std::vector<std::string> lines;
std::map<std::string, bool> numeric_features;
std::vector<std::pair<std::string, std::string>> attributes;
std::string className;
std::string classType;
std::vector<std::vector<float>> X;
std::vector<std::vector<std::string>> Xs;
std::vector<int> y;
std::map<std::string, std::vector<std::string>> states;
private:
void preprocessDataset(int labelIndex)
{
//
// Learn the numeric features
//
numeric_features.clear();
for (const auto& attribute : attributes) {
auto feature = attribute.first;
if (feature == className)
continue;
auto values = attribute.second;
std::transform(values.begin(), values.end(), values.begin(), ::toupper);
numeric_features[feature] = values == "REAL" || values == "INTEGER" || values == "NUMERIC";
}
}
std::vector<int> factorize(const std::string feature, const std::vector<std::string>& labels_t)
{
std::vector<int> yy;
labels.clear();
states.at(feature).clear();
yy.reserve(labels_t.size());
std::map<std::string, int> labelMap;
int i = 0;
@@ -77,54 +118,46 @@ public:
labelMap[label] = i++;
bool allDigits = std::all_of(label.begin(), label.end(), ::isdigit);
if (allDigits)
labels.push_back("Class " + label);
states[feature].push_back("Class " + label);
else
labels.push_back(label);
states[feature].push_back(label);
}
yy.push_back(labelMap[label]);
}
return yy;
};
std::string version() const { return VERSION; };
protected:
std::vector<std::string> lines;
std::vector<std::pair<std::string, std::string>> attributes;
std::string className;
std::string classType;
std::vector<std::vector<float>> X;
std::vector<int> y;
std::vector<std::string> labels;
private:
}
void generateDataset(int labelIndex)
{
X = std::vector<std::vector<float>>(attributes.size(), std::vector<float>(lines.size()));
Xs = std::vector<std::vector<std::string>>(attributes.size(), std::vector<std::string>(lines.size()));
auto yy = std::vector<std::string>(lines.size(), "");
auto removeLines = std::vector<int>(); // Lines with missing values
for (size_t i = 0; i < lines.size(); i++) {
std::stringstream ss(lines[i]);
std::string value;
int pos = 0;
int xIndex = 0;
while (getline(ss, value, ',')) {
auto tokens = split(lines[i], ',');
for (const auto& token : tokens) {
if (pos++ == labelIndex) {
yy[i] = value;
yy[i] = token;
} else {
if (value == "?") {
X[xIndex++][i] = -1;
removeLines.push_back(i);
} else
X[xIndex++][i] = stof(value);
if (numeric_features[attributes[xIndex].first]) {
X[xIndex][i] = stof(token);
} else {
Xs[xIndex][i] = token;
}
xIndex++;
}
}
}
for (auto i : removeLines) {
yy.erase(yy.begin() + i);
for (auto& x : X) {
x.erase(x.begin() + i);
for (size_t i = 0; i < attributes.size(); i++) {
if (!numeric_features[attributes[i].first]) {
auto data = factorize(attributes[i].first, Xs[i]);
std::transform(data.begin(), data.end(), X[i].begin(), [](int x) { return float(x);});
}
}
y = factorize(yy);
};
y = factorize(className, yy);
}
void loadCommon(std::string fileName)
{
std::ifstream file(fileName);
@@ -152,12 +185,19 @@ private:
if (line[0] == '@') {
continue;
}
if (line.find("?", 0) != std::string::npos) {
// ignore lines with missing values
continue;
}
lines.push_back(line);
}
file.close();
for (const auto& attribute : attributes) {
states[attribute.first] = std::vector<std::string>();
}
if (attributes.empty())
throw std::invalid_argument("No attributes found");
};
}
};
#endif
#endif

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@@ -5,6 +5,34 @@ All notable changes to this project will be documented in this file.
The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
## [1.2.0] 2025-06-27 Refactoring and Improvements
### Added
- Refactored code to improve readability and maintainability
- Improved error handling with exceptions
- Claude TECHNICAL_REPORT.md for detailed analysis
- Claude CLAUDE.md for AI engine usage
- Actions to build and upload the conan package to Cimmeria
## [1.1.0] 2024-07-24 String Values in Features
### Added
- Allow string values in features
- Library logo
### Fixed
- Fixed bug in numeric attributes states
### Removed
- Catch2 git submodule
- iostream include
## [1.0.0] 2024-05-21 Initial Release
### Added

83
CLAUDE.md Normal file
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@@ -0,0 +1,83 @@
# CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
## Project Overview
ArffFiles is a header-only C++ library for reading ARFF (Attribute-Relation File Format) files and converting them into STL vectors. The library handles both numeric and categorical features, automatically factorizing categorical attributes.
## Build System
This project uses CMake with Conan for package management:
- **CMake**: Primary build system (requires CMake 3.20+)
- **Conan**: Package management for dependencies
- **Makefile**: Convenience wrapper for common tasks
## Common Development Commands
### Building and Testing
```bash
# Build and run tests (recommended)
make build && make test
# Alternative manual build process
mkdir build_debug
cmake -S . -B build_debug -D CMAKE_BUILD_TYPE=Debug -D ENABLE_TESTING=ON -D CODE_COVERAGE=ON
cmake --build build_debug -t unit_tests_arffFiles -j 16
cd build_debug/tests && ./unit_tests_arffFiles
```
### Testing Options
```bash
# Run tests with verbose output
make test opt="-s"
# Clean test artifacts
make clean
```
### Code Coverage
Code coverage is enabled when building with `-D CODE_COVERAGE=ON` and `-D ENABLE_TESTING=ON`. Coverage reports are generated during test runs.
## Architecture
### Core Components
**Single Header Library**: `ArffFiles.hpp` contains the complete implementation.
**Main Class**: `ArffFiles`
- Header-only design for easy integration
- Handles ARFF file parsing and data conversion
- Automatically determines numeric vs categorical features
- Supports flexible class attribute positioning
### Key Methods
- `load(fileName, classLast=true)`: Load with class attribute at end/beginning
- `load(fileName, className)`: Load with specific named class attribute
- `getX()`: Returns feature vectors as `std::vector<std::vector<float>>`
- `getY()`: Returns labels as `std::vector<int>`
- `getNumericAttributes()`: Returns feature type mapping
### Data Processing Pipeline
1. **File Parsing**: Reads ARFF format, extracts attributes and data
2. **Feature Detection**: Automatically identifies numeric vs categorical attributes
3. **Preprocessing**: Handles missing values (lines with '?' are skipped)
4. **Factorization**: Converts categorical features to numeric codes
5. **Dataset Generation**: Creates final X (features) and y (labels) vectors
### Dependencies
- **Catch2**: Testing framework (fetched via CMake FetchContent)
- **Standard Library**: Uses STL containers (vector, map, string)
- **C++17**: Minimum required standard
### Test Structure
- Tests located in `tests/` directory
- Sample ARFF files in `tests/data/`
- Single test executable: `unit_tests_arffFiles`
- Uses Catch2 v3.3.2 for test framework
### Conan Integration
The project includes a `conanfile.py` that:
- Automatically extracts version from CMakeLists.txt
- Packages as a header-only library
- Exports only the main header file

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@@ -41,7 +41,12 @@ add_subdirectory(config)
# -------
if (ENABLE_TESTING)
MESSAGE("Testing enabled")
add_git_submodule("tests/lib/catch2")
Include(FetchContent)
FetchContent_Declare(Catch2
GIT_REPOSITORY https://github.com/catchorg/Catch2.git
GIT_TAG v3.3.2
)
FetchContent_MakeAvailable(Catch2)
include(CTest)
add_subdirectory(tests)
endif (ENABLE_TESTING)

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@@ -1,6 +1,6 @@
SHELL := /bin/bash
.DEFAULT_GOAL := help
.PHONY: help build test clean
.PHONY: help build test clean conan-build conan-upload
f_debug = build_debug
test_targets = unit_tests_arffFiles
@@ -44,6 +44,16 @@ test: ## Run tests (opt="-s") to verbose output the tests
done
@echo ">>> Done";
conan-build: ## Build Conan package locally
@echo ">>> Building Conan package...";
@conan create . --profile default
@echo ">>> Done";
conan-upload: ## Upload package to Cimmeria JFrog Artifactory
@echo ">>> Uploading to Cimmeria JFrog Artifactory...";
@conan upload arff-files --all -r Cimmeria --confirm
@echo ">>> Done";
help: ## Show help message
@IFS=$$'\n' ; \
help_lines=(`fgrep -h "##" $(MAKEFILE_LIST) | fgrep -v fgrep | sed -e 's/\\$$//' | sed -e 's/##/:/'`); \

209
README.md
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@@ -1,14 +1,211 @@
# ArffFiles
# <img src="logo.png" alt="logo" width="50"/> ArffFiles
![C++](https://img.shields.io/badge/c++-%2300599C.svg?style=flat&logo=c%2B%2B&logoColor=white)
[![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](<https://opensource.org/licenses/MIT>)
![Gitea Release](https://img.shields.io/gitea/v/release/rmontanana/arfffiles?gitea_url=https://gitea.rmontanana.es:3000)
![Gitea Last Commit](https://img.shields.io/gitea/last-commit/rmontanana/arfffiles?gitea_url=https://gitea.rmontanana.es:3000&logo=gitea)
![Gitea Release](https://img.shields.io/gitea/v/release/rmontanana/arfffiles?gitea_url=https://gitea.rmontanana.es)
![Gitea Last Commit](https://img.shields.io/gitea/last-commit/rmontanana/arfffiles?gitea_url=https://gitea.rmontanana.es&logo=gitea)
Header-only library to read Arff Files and return STL vectors with the data read.
A modern C++17 header-only library to read **ARFF (Attribute-Relation File Format)** files and convert them into STL vectors for machine learning and data analysis applications.
### Tests
## Features
- 🔧 **Header-only**: Simply include `ArffFiles.hpp` - no compilation required
- 🚀 **Modern C++17**: Clean, efficient implementation using modern C++ standards
- 🔄 **Automatic Type Detection**: Distinguishes between numeric and categorical attributes
- 📊 **Flexible Class Positioning**: Support for class attributes at any position
- 🎯 **STL Integration**: Returns standard `std::vector` containers for seamless integration
- 🧹 **Data Cleaning**: Automatically handles missing values (lines with '?' are skipped)
- 🏷️ **Label Encoding**: Automatic factorization of categorical features into numeric codes
## Requirements
- **C++17** compatible compiler
- **Standard Library**: Uses STL containers (no external dependencies)
## Installation
### Using Conan
```bash
make build && make test
# Add the package to your conanfile.txt
[requires]
arff-files/1.0.1
# Or install directly
conan install arff-files/1.0.1@
```
### Manual Installation
Simply download `ArffFiles.hpp` and include it in your project:
```cpp
#include "ArffFiles.hpp"
```
## Quick Start
```cpp
#include "ArffFiles.hpp"
#include <iostream>
int main() {
ArffFiles arff;
// Load ARFF file (class attribute at the end by default)
arff.load("dataset.arff");
// Get feature matrix and labels
auto& X = arff.getX(); // std::vector<std::vector<float>>
auto& y = arff.getY(); // std::vector<int>
std::cout << "Dataset size: " << arff.getSize() << " samples" << std::endl;
std::cout << "Features: " << X.size() << std::endl;
std::cout << "Classes: " << arff.getLabels().size() << std::endl;
return 0;
}
```
## API Reference
### Loading Data
```cpp
// Load with class attribute at the end (default)
arff.load("dataset.arff");
// Load with class attribute at the beginning
arff.load("dataset.arff", false);
// Load with specific named class attribute
arff.load("dataset.arff", "class_name");
```
### Accessing Data
```cpp
// Get feature matrix (each inner vector is a feature, not a sample)
std::vector<std::vector<float>>& X = arff.getX();
// Get labels (encoded as integers)
std::vector<int>& y = arff.getY();
// Get dataset information
std::string className = arff.getClassName();
std::vector<std::string> labels = arff.getLabels();
unsigned long size = arff.getSize();
// Get attribute information
auto attributes = arff.getAttributes(); // std::vector<std::pair<std::string, std::string>>
auto numericFeatures = arff.getNumericAttributes(); // std::map<std::string, bool>
```
### Utility Methods
```cpp
// Get library version
std::string version = arff.version();
// Access raw lines (after preprocessing)
std::vector<std::string> lines = arff.getLines();
// Get label states mapping
auto states = arff.getStates(); // std::map<std::string, std::vector<std::string>>
```
## Data Processing Pipeline
1. **File Parsing**: Reads ARFF format, extracts `@attribute` declarations and data
2. **Missing Value Handling**: Skips lines containing `?` (missing values)
3. **Feature Type Detection**: Automatically identifies `REAL`, `INTEGER`, `NUMERIC` vs categorical
4. **Label Positioning**: Handles class attributes at any position in the data
5. **Factorization**: Converts categorical features and labels to numeric codes
6. **Data Organization**: Creates feature matrix `X` and label vector `y`
## Example: Complete Workflow
```cpp
#include "ArffFiles.hpp"
#include <iostream>
int main() {
try {
ArffFiles arff;
arff.load("iris.arff");
// Display dataset information
std::cout << "Dataset: " << arff.getClassName() << std::endl;
std::cout << "Samples: " << arff.getSize() << std::endl;
std::cout << "Features: " << arff.getX().size() << std::endl;
// Show class labels
auto labels = arff.getLabels();
std::cout << "Classes: ";
for (const auto& label : labels) {
std::cout << label << " ";
}
std::cout << std::endl;
// Show which features are numeric
auto numericFeatures = arff.getNumericAttributes();
for (const auto& [feature, isNumeric] : numericFeatures) {
std::cout << feature << ": " << (isNumeric ? "numeric" : "categorical") << std::endl;
}
} catch (const std::exception& e) {
std::cerr << "Error: " << e.what() << std::endl;
return 1;
}
return 0;
}
```
## Supported ARFF Features
- ✅ Numeric attributes (`@attribute feature REAL/INTEGER/NUMERIC`)
- ✅ Categorical attributes (`@attribute feature {value1,value2,...}`)
- ✅ Comments (lines starting with `%`)
- ✅ Missing values (automatic skipping of lines with `?`)
- ✅ Flexible class attribute positioning
- ✅ Case-insensitive attribute declarations
## Error Handling
The library throws `std::invalid_argument` exceptions for:
- Unable to open file
- No attributes found in file
- Specified class name not found
## Development
### Building and Testing
```bash
# Build and run tests
make build && make test
# Run tests with verbose output
make test opt="-s"
# Clean test artifacts
make clean
```
### Using CMake Directly
```bash
mkdir build_debug
cmake -S . -B build_debug -D CMAKE_BUILD_TYPE=Debug -D ENABLE_TESTING=ON
cmake --build build_debug -t unit_tests_arffFiles
cd build_debug/tests && ./unit_tests_arffFiles
```
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
## Contributing
Contributions are welcome! Please feel free to submit a Pull Request.

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TECHNICAL_REPORT.md Normal file
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@@ -0,0 +1,242 @@
# ArffFiles Library - Technical Analysis Report
**Generated**: 2025-06-27
**Version Analyzed**: 1.1.0
**Library Type**: Header-only C++17 ARFF File Parser
## Executive Summary
The ArffFiles library is a functional header-only C++17 implementation for parsing ARFF (Attribute-Relation File Format) files. While it successfully accomplishes its core purpose, several significant weaknesses in design, performance, and robustness have been identified that could impact production use.
**Overall Assessment**: ⚠️ **MODERATE RISK** - Functional but requires improvements for production use.
---
## 🟢 Strengths
### 1. **Architectural Design**
-**Header-only**: Easy integration, no compilation dependencies
-**Modern C++17**: Uses appropriate standard library features
-**Clear separation**: Public/protected/private access levels well-defined
-**STL Integration**: Returns standard containers for seamless integration
### 2. **Functionality**
-**Flexible class positioning**: Supports class attributes at any position
-**Automatic type detection**: Distinguishes numeric vs categorical attributes
-**Missing value handling**: Skips lines with '?' characters
-**Label encoding**: Automatic factorization of categorical features
-**Case-insensitive parsing**: Handles @ATTRIBUTE/@attribute variations
### 3. **API Usability**
-**Multiple load methods**: Three different loading strategies
-**Comprehensive getters**: Good access to internal data structures
-**Utility functions**: Includes trim() and split() helpers
### 4. **Testing Coverage**
-**Real datasets**: Tests with iris, glass, adult, and Japanese vowels datasets
-**Edge cases**: Tests different class positioning scenarios
-**Data validation**: Verifies parsing accuracy with expected values
---
## 🔴 Critical Weaknesses
### 1. **Memory Management & Performance Issues**
#### **Inefficient Data Layout** (HIGH SEVERITY)
```cpp
// Line 131: Inefficient memory allocation
X = std::vector<std::vector<float>>(attributes.size(), std::vector<float>(lines.size()));
```
- **Problem**: Feature-major layout instead of sample-major
- **Impact**: Poor cache locality, inefficient for ML algorithms
- **Memory overhead**: Double allocation for `X` and `Xs` vectors
- **Performance**: Suboptimal for large datasets
#### **Redundant Memory Usage** (MEDIUM SEVERITY)
```cpp
std::vector<std::vector<float>> X; // Line 89
std::vector<std::vector<std::string>> Xs; // Line 90
```
- **Problem**: Maintains both numeric and string representations
- **Impact**: 2x memory usage for categorical features
- **Memory waste**: `Xs` could be deallocated after factorization
#### **No Memory Pre-allocation** (MEDIUM SEVERITY)
- **Problem**: Multiple vector resizing during parsing
- **Impact**: Memory fragmentation and performance degradation
### 2. **Error Handling & Robustness**
#### **Unsafe Type Conversions** (HIGH SEVERITY)
```cpp
// Line 145: No exception handling
X[xIndex][i] = stof(token);
```
- **Problem**: `stof()` can throw `std::invalid_argument` or `std::out_of_range`
- **Impact**: Program termination on malformed numeric data
- **Missing validation**: No checks for valid numeric format
#### **Insufficient Input Validation** (HIGH SEVERITY)
```cpp
// Line 39: Unsafe comparison without bounds checking
for (int i = 0; i < attributes.size(); ++i)
```
- **Problem**: No validation of file structure integrity
- **Missing checks**:
- Empty attribute names
- Duplicate attribute names
- Malformed attribute declarations
- Inconsistent number of tokens per line
#### **Resource Management** (MEDIUM SEVERITY)
```cpp
// Line 163-194: No RAII for file handling
std::ifstream file(fileName);
// ... processing ...
file.close(); // Manual close
```
- **Problem**: Manual file closing (though acceptable here)
- **Potential issue**: No exception safety guarantee
### 3. **Algorithm & Design Issues**
#### **Inefficient String Processing** (MEDIUM SEVERITY)
```cpp
// Line 176-182: Inefficient attribute parsing
std::stringstream ss(line);
ss >> keyword >> attribute;
type = "";
while (ss >> type_w)
type += type_w + " "; // String concatenation in loop
```
- **Problem**: Repeated string concatenation is O(n²)
- **Impact**: Performance degradation on large files
- **Solution needed**: Use string reserve or stringstream
#### **Suboptimal Lookup Performance** (LOW SEVERITY)
```cpp
// Line 144: Map lookup in hot path
if (numeric_features[attributes[xIndex].first])
```
- **Problem**: Hash map lookup for every data point
- **Impact**: Unnecessary overhead during dataset generation
### 4. **API Design Limitations**
#### **Return by Value Issues** (MEDIUM SEVERITY)
```cpp
// Line 55-60: Expensive copies
std::vector<std::string> getLines() const { return lines; }
std::map<std::string, std::vector<std::string>> getStates() const { return states; }
```
- **Problem**: Large object copies instead of const references
- **Impact**: Unnecessary memory allocation and copying
- **Performance**: O(n) copy cost for large datasets
#### **Non-const Correctness** (MEDIUM SEVERITY)
```cpp
// Line 68-69: Mutable references without const alternatives
std::vector<std::vector<float>>& getX() { return X; }
std::vector<int>& getY() { return y; }
```
- **Problem**: No const versions for read-only access
- **Impact**: API design inconsistency, potential accidental modification
#### **Type Inconsistency** (LOW SEVERITY)
```cpp
// Line 56: Mixed return types
unsigned long int getSize() const { return lines.size(); }
```
- **Problem**: Should use `size_t` or `std::size_t`
- **Impact**: Type conversion warnings on some platforms
### 5. **Thread Safety**
#### **Not Thread-Safe** (MEDIUM SEVERITY)
- **Problem**: No synchronization mechanisms
- **Impact**: Unsafe for concurrent access
- **Missing**: Thread-safe accessors or documentation warning
### 6. **Security Considerations**
#### **Path Traversal Vulnerability** (LOW SEVERITY)
```cpp
// Line 161: No path validation
void loadCommon(std::string fileName)
```
- **Problem**: No validation of file path
- **Impact**: Potential directory traversal if user input not sanitized
- **Mitigation**: Application-level validation needed
#### **Resource Exhaustion** (MEDIUM SEVERITY)
- **Problem**: No limits on file size or memory usage
- **Impact**: Potential DoS with extremely large files
- **Missing**: File size validation and memory limits
### 7. **ARFF Format Compliance**
#### **Limited Format Support** (MEDIUM SEVERITY)
- **Missing features**:
- Date attributes (`@attribute date "yyyy-MM-dd HH:mm:ss"`)
- String attributes (`@attribute text string`)
- Relational attributes (nested ARFF)
- Sparse data format (`{0 X, 3 Y, 5 Z}`)
#### **Parsing Edge Cases** (LOW SEVERITY)
```cpp
// Line 188: Simplistic missing value detection
if (line.find("?", 0) != std::string::npos)
```
- **Problem**: Doesn't handle quoted '?' characters
- **Impact**: May incorrectly skip valid data containing '?' in strings
---
## 🔧 Recommended Improvements
### High Priority
1. **Add exception handling** around `stof()` calls
2. **Implement proper input validation** for malformed data
3. **Fix memory layout** to sample-major organization
4. **Add const-correct API methods**
5. **Optimize string concatenation** in parsing
### Medium Priority
1. **Implement RAII** patterns consistently
2. **Add memory usage limits** and validation
3. **Provide const reference getters** for large objects
4. **Document thread safety** requirements
5. **Add comprehensive error reporting**
### Low Priority
1. **Extend ARFF format support** (dates, strings, sparse)
2. **Optimize lookup performance** with cached indices
3. **Add file path validation**
4. **Implement move semantics** for performance
---
## 📊 Performance Metrics (Estimated)
| Dataset Size | Memory Overhead | Performance Impact |
|--------------|-----------------|-------------------|
| Small (< 1MB) | ~200% | Negligible |
| Medium (10MB) | ~300% | Moderate |
| Large (100MB+) | ~400% | Significant |
**Note**: Overhead includes duplicate storage and inefficient layout.
---
## 🎯 Conclusion
The ArffFiles library successfully implements core ARFF parsing functionality but suffers from several design and implementation issues that limit its suitability for production environments. The most critical concerns are:
1. **Lack of robust error handling** leading to potential crashes
2. **Inefficient memory usage** limiting scalability
3. **Performance issues** with large datasets
While functional for small to medium datasets in controlled environments, significant refactoring would be required for production use with large datasets or untrusted input.
**Recommendation**: Consider this library suitable for prototyping and small-scale applications, but plan for refactoring before production deployment.

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@@ -137,7 +137,7 @@
include(CMakeParseArguments)
option(CODE_COVERAGE_VERBOSE "Verbose information" FALSE)
option(CODE_COVERAGE_VERBOSE "Verbose information" TRUE)
# Check prereqs
find_program( GCOV_PATH gcov )
@@ -160,7 +160,11 @@ foreach(LANG ${LANGUAGES})
endif()
elseif(NOT "${CMAKE_${LANG}_COMPILER_ID}" MATCHES "GNU"
AND NOT "${CMAKE_${LANG}_COMPILER_ID}" MATCHES "(LLVM)?[Ff]lang")
message(FATAL_ERROR "Compiler is not GNU or Flang! Aborting...")
if ("${LANG}" MATCHES "CUDA")
message(STATUS "Ignoring CUDA")
else()
message(FATAL_ERROR "Compiler is not GNU or Flang! Aborting...")
endif()
endif()
endforeach()

43
conanfile.py Normal file
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@@ -0,0 +1,43 @@
import re
from conan import ConanFile
from conan.tools.files import copy
class ArffFilesConan(ConanFile):
name = "arff-files"
version = "X.X.X"
description = (
"Header-only library to read ARFF (Attribute-Relation File Format) files and return STL vectors with the data read."
)
url = "https://github.com/rmontanana/ArffFiles"
license = "MIT"
homepage = "https://github.com/rmontanana/ArffFiles"
topics = ("arff", "data-processing", "file-parsing", "header-only", "cpp17")
no_copy_source = True
exports_sources = "ArffFiles.hpp", "LICENSE", "README.md"
package_type = "header-library"
def init(self):
# Read the CMakeLists.txt file to get the version
with open("CMakeLists.txt", "r") as f:
lines = f.readlines()
for line in lines:
if "VERSION" in line:
# Extract the version number using regex
match = re.search(r"VERSION\s+(\d+\.\d+\.\d+)", line)
if match:
self.version = match.group(1)
def package(self):
# Copy header file to include directory
copy(self, "*.hpp", src=self.source_folder, dst=self.package_folder, keep_path=False)
# Copy license and readme for package documentation
copy(self, "LICENSE", src=self.source_folder, dst=self.package_folder, keep_path=False)
copy(self, "README.md", src=self.source_folder, dst=self.package_folder, keep_path=False)
def package_info(self):
# Header-only library configuration
self.cpp_info.bindirs = []
self.cpp_info.libdirs = []
# Set include directory (header will be in package root)
self.cpp_info.includedirs = ["."]

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@@ -18,7 +18,7 @@ public:
TEST_CASE("Version Test", "[ArffFiles]")
{
ArffFiles arff;
REQUIRE(arff.version() == "1.0.0");
REQUIRE(arff.version() == "1.1.0");
}
TEST_CASE("Load Test", "[ArffFiles]")
{
@@ -65,14 +65,14 @@ TEST_CASE("Load Test", "[ArffFiles]")
TEST_CASE("Load with class name", "[ArffFiles]")
{
ArffFiles arff;
arff.load(Paths::datasets("glass"), "Type");
arff.load(Paths::datasets("glass"), std::string("Type"));
REQUIRE(arff.getClassName() == "Type");
REQUIRE(arff.getClassType() == "{ 'build wind float', 'build wind non-float', 'vehic wind float', 'vehic wind non-float', containers, tableware, headlamps}");
REQUIRE(arff.getLabels().size() == 6);
REQUIRE(arff.getLabels()[0] == "'build wind float'");
REQUIRE(arff.getLabels()[1] == "'vehic wind float'");
REQUIRE(arff.getLabels()[0] == "build wind float");
REQUIRE(arff.getLabels()[1] == "vehic wind float");
REQUIRE(arff.getLabels()[2] == "tableware");
REQUIRE(arff.getLabels()[3] == "'build wind non-float'");
REQUIRE(arff.getLabels()[3] == "build wind non-float");
REQUIRE(arff.getLabels()[4] == "headlamps");
REQUIRE(arff.getLabels()[5] == "containers");
REQUIRE(arff.getSize() == 214);
@@ -108,12 +108,41 @@ TEST_CASE("Load with class name as first attribute", "[ArffFiles]")
{1.86094, 1.89165, 1.93921, 1.71752},
{-0.207383, -0.193249, -0.239664, -0.218572} }
};
auto X = arff.getX();
for (int i = 0; i < 4; ++i) {
for (int j = 0; j < 4; ++j)
REQUIRE(arff.getX()[i][j] == Catch::Approx(expected[i][j]));
REQUIRE(X[i][j] == Catch::Approx(expected[i][j]));
}
auto expected_y = std::vector<int>{ 0, 0, 0, 0 };
for (int i = 120; i < 124; ++i)
REQUIRE(arff.getY()[i] == expected_y[i - 120]);
}
TEST_CASE("Adult dataset", "[ArffFiles]")
{
ArffFiles arff;
arff.load(Paths::datasets("adult"), std::string("class"));
REQUIRE(arff.getClassName() == "class");
REQUIRE(arff.getClassType() == "{ >50K, <=50K }");
REQUIRE(arff.getLabels().size() == 2);
REQUIRE(arff.getLabels()[0] == "<=50K");
REQUIRE(arff.getLabels()[1] == ">50K");
REQUIRE(arff.getSize() == 45222);
REQUIRE(arff.getLines().size() == 45222);
REQUIRE(arff.getLines()[0] == "25, Private, 226802, 11th, 7, Never-married, Machine-op-inspct, Own-child, Black, Male, 0, 0, 40, United-States, <=50K");
auto X = arff.getX();
REQUIRE(X[0][0] == 25);
REQUIRE(X[1][0] == 0);
REQUIRE(X[2][0] == 226802);
REQUIRE(X[3][0] == 0);
REQUIRE(X[4][0] == 7);
REQUIRE(X[5][0] == 0);
REQUIRE(X[6][0] == 0);
REQUIRE(X[7][0] == 0);
REQUIRE(X[8][0] == 0);
REQUIRE(X[9][0] == 0);
REQUIRE(X[10][0] == 0);
REQUIRE(X[11][0] == 0);
REQUIRE(X[12][0] == 40);
REQUIRE(X[13][0] == 0);
}

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