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摘要翻译：
是大型软件源代码层次聚类的高质量算法。这有效地打破了数千万行源代码的复杂性，使得人类软件工程师可以通过查看软件系统的源代码自动重构的体系结构图来高层次地理解软件系统。体系结构图显示了一个子系统树，树叶中有OOP类（换句话说，一个嵌套的软件分解）。该工具从软件系统的源代码中重建缺少的（不一致/不完整/不存在的）体系结构文档。这有助于软件维护：变更请求的执行速度大大加快。简单地说，这个独特的工具允许将面向对象软件系统的可理解层次从面向对象的类级提升到子系统级。据估计，在这项工作的基础上开发的一个商业工具将把软件维护费用减少10倍于目前的需要，并将允许实施下一代软件系统，这些系统目前过于复杂，无法在人类的理解范围内，因此还无法设计或实施。开源实现原型：http://sourceforge.net/p/insoar/code-0/1/tree/
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英文标题：
《An efficient high-quality hierarchical clustering algorithm for
automatic inference of software architecture from the source code of a
software system》
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作者：
Sarge Rogatch
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最新提交年份：
2012
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分类信息：
一级分类：Computer Science 计算机科学
二级分类：Artificial Intelligence 人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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一级分类：Computer Science 计算机科学
二级分类：Machine Learning 机器学习
分类描述：Papers on all aspects of machine learning research (supervised, unsupervised, reinforcement learning, bandit problems, and so on) including also robustness, explanation, fairness, and methodology. cs.LG is also an appropriate primary category for applications of machine learning methods.
关于机器学习研究的所有方面的论文（有监督的，无监督的，强化学习，强盗问题，等等），包括健壮性，解释性，公平性和方法论。对于机器学习方法的应用，CS.LG也是一个合适的主要类别。
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一级分类：Computer Science 计算机科学
二级分类：Software Engineering 软件工程
分类描述：Covers design tools, software metrics, testing and debugging, programming environments, etc. Roughly includes material in all of ACM Subject Classes D.2, except that D.2.4 (program verification) should probably have Logics in Computer Science as the primary subject area.
涵盖设计工具、软件度量、测试和调试、编程环境等。大致包括ACM所有主题课程D.2的材料，除了D.2.4（程序验证）可能应该有计算机科学中的逻辑作为主要主题领域。
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英文摘要：
It is a high-quality algorithm for hierarchical clustering of large software source code. This effectively allows to break the complexity of tens of millions lines of source code, so that a human software engineer can comprehend a software system at high level by means of looking at its architectural diagram that is reconstructed automatically from the source code of the software system. The architectural diagram shows a tree of subsystems having OOP classes in its leaves (in the other words, a nested software decomposition). The tool reconstructs the missing (inconsistent/incomplete/inexistent) architectural documentation for a software system from its source code. This facilitates software maintenance: change requests can be performed substantially faster. Simply speaking, this unique tool allows to lift the comprehensible grain of object-oriented software systems from OOP class-level to subsystem-level. It is estimated that a commercial tool, developed on the basis of this work, will reduce software maintenance expenses 10 times on the current needs, and will allow to implement next-generation software systems which are currently too complex to be within the range of human comprehension, therefore can't yet be designed or implemented. Implemented prototype in Open Source: http://sourceforge.net/p/insoar/code-0/1/tree/
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PDF链接：
https://arxiv.org/pdf/1202.3335
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