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This paper presents a trustworthiness measurement model for open source software (OSS) trustworthiness assessment. The model decomposes trustworthiness attributes at the source code level and evaluates contributor contribution values. By quantifying attributes such as security, maintainability, reliability, testability, and compatibility, and introducing a novel method for measuring contributor impact based on Abstract Syntax Trees (ASTs), our model provides a holistic view of OSS trustworthiness. Through contributor segmentation and weight assignment, it reflects the varying influence of contributors. Experimental validation using Huawei’s OpenEuler OSS demonstrates the model’s effectiveness, bridging theory and practice in OSS quality assurance and empowering stakeholders in critical system decisions.

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A Contributor-Based Segmentation Model for Open Source Software Source Code Trustworthiness Measurement

  • 会议论文

  • 发表日期：

    2025年

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  • Xuecheng Hou,
  • Yixiang Chen,
  • Jianxun Wang

摘要

This paper presents a trustworthiness measurement model for open source software (OSS) trustworthiness assessment. The model decomposes trustworthiness attributes at the source code level and evaluates contributor contribution values. By quantifying attributes such as security, maintainability, reliability, testability, and compatibility, and introducing a novel method for measuring contributor impact based on Abstract Syntax Trees (ASTs), our model provides a holistic view of OSS trustworthiness. Through contributor segmentation and weight assignment, it reflects the varying influence of contributors. Experimental validation using Huawei’s OpenEuler OSS demonstrates the model’s effectiveness, bridging theory and practice in OSS quality assurance and empowering stakeholders in critical system decisions.