Datasets:
Tasks:
Tabular Classification
Sub-tasks:
multi-class-classification
Languages:
English
Size:
1M<n<10M
Tags:
source-code
software-engineering
defect-prediction
transfer-learning
static-analysis
c-language
License:
| annotations_creators: | |
| - expert-generated | |
| language: | |
| - en | |
| license: cc-by-4.0 | |
| pretty_name: Cross-Project Defect Prediction (CPDP) Dataset — C & Java Projects | |
| size_categories: | |
| - 1M<n<10M | |
| source_datasets: | |
| - original | |
| tags: | |
| - source-code | |
| - software-engineering | |
| - defect-prediction | |
| - transfer-learning | |
| - static-analysis | |
| - c-language | |
| - java | |
| task_categories: | |
| - tabular-classification | |
| task_ids: | |
| - multi-class-classification | |
| # 🧩 Cross-Project Defect Prediction (CPDP) Dataset — C & Java Projects | |
| This repository hosts a **custom dataset** for **Cross-Project Defect Prediction (CPDP)** research, curated from a diverse collection of real-world open-source projects written in **C (441 projects)** and **Java (98 projects)**. | |
| The dataset aims to support research on **software defect prediction, transfer learning**, and **imbalanced data handling** across heterogeneous programming environments. | |
| --- | |
| ## 📘 Overview | |
| | Language | #Projects | Description | | |
| |-----------|------------|-------------| | |
| | **C** | 441 | Includes diverse open-source repositories from various domains | | |
| | **Java** | 98 | Covers projects from academic domains collected from GitHub and other public repositories | | |
| Each project folder typically includes: | |
| - Source code files (`.c`, `.h`, `.java`) | |
| - Bug/defect labels (where available) | |
| - Metadata (e.g., LOC, complexity, commits) | |
| - Preprocessed CSV feature files for ML models | |
| --- | |
| ## 🎯 Purpose | |
| The dataset is designed for: | |
| - **Cross-Project Defect Prediction (CPDP)** | |
| - **Transfer Learning** and **Domain Adaptation** studies | |
| - **Feature engineering** on static code metrics | |
| - **Benchmarking** new software defect prediction models | |
| --- | |
| ## 🧠Suggested Research Directions | |
| - Comparison of **within-project vs cross-project** prediction accuracy | |
| - Study of **language heterogeneity** in CPDP (C ↔ Java transfer) | |
| - Use of **oversampling** or **class balancing** methods (e.g., SMOTE, OTOMO) | |
| - Integration with **Bayesian Networks**, **Deep Learning**, or **Tensor-based** models | |