SQuaD: The Software Quality Dataset

TL;DR

SQuaD is a comprehensive, multi-dimensional dataset of software quality metrics from 450 open-source projects, enabling large-scale empirical research on software maintainability, evolution, and quality assessment.

Contribution

It introduces a unified, multi-source dataset with over 700 metrics across diverse projects, integrating version history, vulnerability data, and process metrics for advanced software quality analysis.

Findings

Enables large-scale empirical studies on software quality.

Supports research on maintainability and technical debt.

Facilitates automated, cross-project quality modeling.

Abstract

Software quality research increasingly relies on large-scale datasets that measure both the product and process aspects of software systems. However, existing resources often focus on limited dimensions, such as code smells, technical debt, or refactoring activity, thereby restricting comprehensive analyses across time and quality dimensions. To address this gap, we present the Software Quality Dataset (SQuaD), a multi-dimensional, time-aware collection of software quality metrics extracted from 450 mature open-source projects across diverse ecosystems, including Apache, Mozilla, FFmpeg, and the Linux kernel. By integrating nine state-of-the-art static analysis tools, i.e., SonarQube, CodeScene, PMD, Understand, CK, JaSoMe, RefactoringMiner, RefactoringMiner++, and PyRef, our dataset unifies over 700 unique metrics at method, class, file, and project levels. Covering a total of 63,586 analyzed project releases, SQuaD also provides version control and issue-tracking histories, software vulnerability data (CVE/CWE), and process metrics proven to enhance Just-In-Time (JIT) defect prediction. The SQuaD enables empirical research on maintainability, technical debt, software evolution, and quality assessment at unprecedented scale. We also outline emerging research directions, including automated dataset updates and cross-project quality modeling to support the continuous evolution of software analytics. The dataset is publicly available on ZENODO (DOI: 10.5281/zenodo.17566690).