With python's ascension as a dominant programming language, particularly in the fields of artificial intelligence and data science, the need for comprehensive datasets focusing on software quality within python pr...
详细信息
ISBN:
(纸本)9798350380279;9798350380262
With python's ascension as a dominant programming language, particularly in the fields of artificial intelligence and data science, the need for comprehensive datasets focusing on software quality within python projects has become increasingly noticeable. This study introduces a detailed dataset designed to address this gap, enriching academic resources in software engineering. The dataset encompasses a wide array of software quality metrics on up to 80 projects, including 51.765.853 SonarQube issues, 268.506 SonarQube code quality metrics, 11.915 software refactoring records, and 155.127 pairs of bug-inducing and bug-fixing commits, along with 863.931 GitHub issue tracker entries. This extensive collection serves as a versatile tool for various research activities, enabling analysis of the relationships between technical debt and software refactorings, correlations between refactoring processes and bug resolution, and their overall impact on software maintainability and reliability. By offering a comprehensive and multifaceted dataset, this study significantly contributes to understanding and improving software quality in python projects.
A static analysis method is one of the popular methods of software code analysis. Such method allows checking the code for compliance with the language specification as well as finding potential vulnerabilities. In th...
详细信息
A static analysis method is one of the popular methods of software code analysis. Such method allows checking the code for compliance with the language specification as well as finding potential vulnerabilities. In this work, a static analysis of a corpus of listings of open-source python applications is performed. Using the Bandit library, statistical values of various categories of potential vulnerabilities are found, and a rating table of vulnerabilities detected in the dataset involved is constructed. A qualitative analysis of threats is performed according to their severity based on the CWE data.
暂无评论