Throughout the history of software, evolution has occurred in cycles of rise and fall driven by competition, and open-source software (OSS) is no exception. This cycle is accelerating, particularly in rapidly evolving domains such as web development and deep learning. However, the impact of competitive relationships among OSS projects on their survival remains unclear, and there are risks of losing a competitive edge to rivals. To address this, this study proposes a new automated method called ``Mutual Impact Analysis of OSS (MIAO)'' to quantify these competitive relationships. The proposed method employs a structural vector autoregressive model and impulse response functions, normally used in macroeconomic analysis, to analyze the interactions among OSS projects. In an empirical analysis involving mining and analyzing 187 OSS project groups, MIAO identified projects that were forced to cease development owing to competitive influences with up to 81\% accuracy, and the resulting features supported predictive experiments that anticipate cessation one year ahead with up to 77\% accuracy. This suggests that MIAO could be a valuable tool for OSS project maintainers to understand the dynamics of OSS ecosystems and predict the rise and fall of OSS projects.

翻译：在软件发展的历史长河中，演化始终遵循着由竞争驱动的兴衰周期，开源软件（OSS）亦不例外。这一周期正在加速，尤其是在Web开发和深度学习等快速演进的领域。然而，OSS项目间的竞争关系对其生存的具体影响尚不明确，且存在被竞争对手超越而丧失竞争优势的风险。为应对此问题，本研究提出了一种名为“OSS相互影响分析（MIAO）”的新型自动化方法，以量化这些竞争关系。该方法采用通常用于宏观经济分析的结构向量自回归模型和脉冲响应函数，来分析OSS项目间的相互作用。在一项涉及挖掘和分析187个OSS项目组的实证分析中，MIAO以高达81%的准确率识别出因竞争影响而被迫停止开发的项目，并且由此产生的特征支持了预测实验，能够以高达77%的准确率提前一年预测项目终止。这表明MIAO可以成为OSS项目维护者理解OSS生态系统动态并预测OSS项目兴衰的宝贵工具。