时间复杂性和软件故障

F. Anger, J. Munson, R. V. Rodríguez
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引用次数: 8

摘要

软件开发人员在开始项目之前使用复杂性度量来预测开发成本,并在系统构建后估计故障的可能性。然而,传统的度量方法主要是为顺序程序设计的,对并发系统增加的复杂性或实时系统增加的需求提供的洞察很少。为了预测开发成本和工作量,CoCoMo模型考虑了诸如实时性和其他性能要求等因素;然而,对于故障预测,大多数复杂性度量都不涉及并发性。提出了开发我们称之为时间复杂性的度量的大纲,包括初步验证的重要和令人鼓舞的结果。软件复杂性的13个标准度量被显示只定义了模块特征中两个不同的变化域。在时间复杂性的10个建议度量中,有6个发现了两个新的方差域。这些新域在软件故障建模中具有预测价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Temporal complexity and software faults
Software developers use complexity metrics to predict development costs before embarking on a project and to estimate the likelihood of faults once the system is built. Traditional measures, however, were designed principally for sequential programs, providing little insight into the added complexity of concurrent systems or increased demands of real-time systems. For the purpose of predicting cost and effort of development, the CoCoMo model considers factors such as real-time and other performance requirements; for fault prediction, however, most complexity metrics are silent on concurrency. An outline for developing a measure of what we term temporal complexity, including significant and encouraging results of preliminary validation, is presented. 13 standard measures of software complexity are shown to define only two distinct domains of variance in module characteristics. Two new domains of variance are uncovered through 6 out of 10 proposed measures of temporal complexity. The new domains are shown to have predictive value in the modeling of software faults.<>
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