标题： Roseau：Java 中基于源代码的快速、准确的 API 破坏性更改分析 显示英文标题

标题： Roseau: Fast, Accurate, Source-based API Breaking Change Analysis in Java

摘要： 理解软件库中的API演化和引入的破坏性变更（BCs）对于库维护者管理向后兼容性以及研究人员进行软件库演化的实证研究至关重要。在Java中，JApiCmp和Revapi等工具常用于检测库版本之间的BCs，但它们依赖于二进制JAR文件，这限制了其适用性。这种限制阻碍了API演化的大规模纵向研究以及细粒度分析，如提交级别的BC检测。在本文中，我们介绍了Roseau，一种新颖的静态分析工具，它能够从配备丰富语义分析的库代码中构建与技术无关的API模型。API模型可以用于研究API演化，并与之比较以识别任何两个库版本（发布、提交、分支等）之间的BCs。与传统方法不同，Roseau可以从源代码或字节码构建API模型，并针对库历史的大规模纵向分析进行了优化。我们评估了Roseau在纵向研究API演化中的准确性、性能和适用性，并以JApiCmp和Revapi作为基准。我们扩展并完善了一个已建立的BCs基准，并表明Roseau的准确性（F1 = 0.99）高于JApiCmp（F1 = 0.86）和Revapi（F1 = 0.91）。我们分析了Maven Central中的60个流行库，并发现Roseau表现出卓越的性能，在不到两秒内检测版本之间的BCs，包括在拥有数十万行代码的库中。我们进一步通过跟踪Google的Guava API的演化以及14年和6,839次提交中BCs的引入，说明了JApiCmp和Revapi在纵向研究中的局限性，以及Roseau提供的新颖分析能力，将分析时间从几天减少到几分钟。 显示英文摘要

摘要： Understanding API evolution and the introduction of breaking changes (BCs) in software libraries is essential for library maintainers to manage backward compatibility and for researchers to conduct empirical studies on software library evolution. In Java, tools such as JApiCmp and Revapi are commonly used to detect BCs between library releases, but their reliance on binary JARs limits their applicability. This restriction hinders large-scale longitudinal studies of API evolution and fine-grained analyses such as commit-level BC detection. In this paper, we introduce Roseau, a novel static analysis tool that constructs technology-agnostic API models from library code equipped with rich semantic analyses. API models can be analyzed to study API evolution and compared to identify BCs between any two versions of a library (releases, commits, branches, etc.). Unlike traditional approaches, Roseau can build API models from source code or bytecode, and is optimized for large-scale longitudinal analyses of library histories. We assess the accuracy, performance, and suitability of Roseau for longitudinal studies of API evolution, using JApiCmp and Revapi as baselines. We extend and refine an established benchmark of BCs and show that Roseau achieves higher accuracy (F1 = 0.99) than JApiCmp (F1 = 0.86) and Revapi (F1 = 0.91). We analyze 60 popular libraries from Maven Central and find that Roseau delivers excellent performance, detecting BCs between versions in under two seconds, including in libraries with hundreds of thousands of lines of code. We further illustrate the limitations of JApiCmp and Revapi for longitudinal studies and the novel analysis capabilities offered by Roseau by tracking the evolution of Google's Guava API and the introduction of BCs over 14 years and 6,839 commits, reducing analysis times from a few days to a few minutes.