Measuring OO systems: a critical analysis of the MOOD metrics

Tobias Mayer, T. Hall
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引用次数: 36

Abstract

In parallel with the rise to prominence of the OO paradigm has come the acceptance that conventional software metrics are not adequate to measure object oriented systems. This has inspired a number of software practitioners and academics to develop new metrics that are suited to the OO paradigm. Arguably, the most thorough treatment of the subject is that of the MOOD team, under the leadership of Abreau. The MOOD metrics have been subjected to much empirical evaluation, with claims made regarding the usefulness of the metrics to assess external attributes such as quality and maintainability. We evaluate the MOOD metrics on a theoretical level and show that any empirical validation is premature, due to the majority of the MOOD metrics being fundamentally flawed. The metrics either fail to meet the MOOD team's own criteria or are founded on an imprecise, and in certain cases inaccurate, view of the OO paradigm. We propose our own solutions to some of these anomalies and clarify some important aspects of OO design, in particular those aspects that may cause difficulties when attempting to define accurate and meaningful metrics. The suggestions we make are not limited to the MOOD metrics but are intended to have a wider applicability in the field of OO metrics.
度量OO系统:对MOOD度量的关键分析
随着OO范式的兴起,人们开始接受传统的软件度量标准不足以度量面向对象的系统。这激发了许多软件从业者和学者开发适合OO范式的新度量标准。可以说,对这个问题最彻底的处理是由阿布鲁领导的MOOD团队。MOOD指标已经受到了许多经验评估,并声称这些指标对于评估外部属性(如质量和可维护性)的有用性。我们在理论层面上评估了MOOD指标,并表明任何经验验证都是不成熟的,因为大多数MOOD指标从根本上存在缺陷。量度要么不能满足MOOD团队自己的标准,要么是建立在不精确的OO范型视图上,在某些情况下是不准确的。我们针对其中一些异常情况提出了自己的解决方案,并阐明了OO设计的一些重要方面,特别是那些在尝试定义准确而有意义的度量时可能导致困难的方面。我们提出的建议并不局限于MOOD指标,而是希望在OO指标领域具有更广泛的适用性。
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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