Validation of measurement tools to extract metrics from open source projects

N. S. A. Bakar, C. Boughton
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引用次数: 13

Abstract

Software measurement can play a major role in ensuring the quality and reliability of software products. The measurement activities require appropriate tools to collect relevant metric data. Currently, there are several such tools available for software measurement. The main objective of this paper is to discuss the validation of results when using a combination of multiple measurement tools especially for products built using object-oriented techniques and languages. In this paper, we highlight four tools for collecting metric data, in our case from several Java-based open source projects. Our findings show that the tools provide different results for similar metrics and we discuss the methods used to validate the results reported by the tools. Our research is currently based on the work of Card and Glass, who argue that design complexity measures (data complexity and structural complexity) are indicators/predictors of procedural/cyclomatic complexity (decision counts) and errors (discovered from system tests).
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验证从开源项目中提取度量标准的度量工具
软件度量在保证软件产品的质量和可靠性方面起着重要的作用。度量活动需要适当的工具来收集相关的度量数据。目前,有几个这样的工具可用于软件测量。本文的主要目的是讨论当使用多种测量工具的组合时,特别是对于使用面向对象技术和语言构建的产品,结果的验证。在本文中,我们重点介绍了收集度量数据的四种工具,在我们的案例中,这些工具来自几个基于java的开源项目。我们的研究结果表明,这些工具为类似的指标提供了不同的结果,我们讨论了用于验证工具报告的结果的方法。我们的研究目前是基于Card和Glass的工作,他们认为设计复杂性度量(数据复杂性和结构复杂性)是程序/圈复杂性(决策计数)和错误(从系统测试中发现)的指示器/预测器。
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