FINALIsT2: Feature identification, localization, and tracing tool

Andreas Burger, Sten Grüner
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引用次数: 8

Abstract

Feature identification and localization is a complicated and error-prone task. Nowadays it is mainly done manually by lead software developer or domain experts. Sometimes these experts are no longer available or cannot support in the feature identification and localization process. Due to that we propose a tool which supports this process with an iterative semi-automatic workflow for identifying, localizing and documenting features. Our tool calculates a feature cluster based on an defined entry point that is found by using information retrieval techniques. This feature cluster will be iteratively refined by the user. This iterative feedback-driven workflow enables developer which are not deeply involved in the development of the software to identify and extract features properly. We evaluated our tool on an industrial smart control system for electric motors with first promising results.
FINALIsT2:特征识别、定位和跟踪工具
特征识别和定位是一项复杂且容易出错的任务。现在它主要是由首席软件开发人员或领域专家手工完成的。有时这些专家不再可用或不能在特征识别和定位过程中提供支持。因此,我们提出了一种工具,它通过迭代的半自动工作流程来支持这一过程,用于识别、本地化和记录功能。我们的工具根据使用信息检索技术找到的定义入口点计算特征集群。这个特征集群将由用户迭代地改进。这种迭代反馈驱动的工作流程使得没有深入参与软件开发的开发人员能够正确地识别和提取特性。我们在电机的工业智能控制系统上评估了我们的工具,并取得了初步的成果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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