利用潜在语义索引恢复架构概念

Pieter Van Der Spek, Steven Klusener, Pierre Van De Laar
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引用次数: 23

摘要

为了解决在源代码中定位高级概念的问题,我们提出使用一种先进的信息检索方法来利用源代码中的语言信息,如变量名和注释。我们的技术是基于潜在语义索引(LSI),这也被用于今天的搜索引擎。然而,将LSI应用于源代码并不是直截了当的。因此,我们的方法不仅包括LSI,还包括其他几种算法和方法。我们讨论了有用的算法和方法,并使用Philips Healthcare的案例研究结果概述了它们的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards Recovering Architectural Concepts Using Latent Semantic Indexing
In order to address the problem of locating high-level concepts in source code we propose to use an advanced information retrieval method to exploit linguistic information found in source code, such as variable names and comments. Our technique is based on latent semantic indexing (LSI) which is also used in today's search engines. Applying LSI to source code, however, is not straightforward. Our approach therefore not only includes LSI, but also several other algorithms and methods. We discuss the algorithms and methods that turned out to be useful and provide an overview of their effects using the results obtained from a case study at Philips Healthcare.
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