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A Quantitative Approach to Software Maintainability Prediction

机译:软件可维护性预测的定量方法

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Software maintainability is one important aspect in the evaluation of software evolution of a software product. Due to the complexity of tracking maintenance behaviors, it is difficult to accurately predict the cost and risk of maintenance after delivery of software products. In an attempt to address this issue quantitatively, software maintainability is viewed as an inevitable evolution process driven by maintenance behaviors, given a health index at the time when a software product are delivered. A Hidden Markov Model (HMM) is used to simulate the maintenance behaviors shown as their possible occurrence probabilities. And software metrics is the measurement of the quality of a software product and its measurement results of a product being delivered are combined to form the health index of the product. The health index works as a weight on the process of maintenance behavior over time. When the occurrence probabilities of maintenance behaviors reach certain number which is reckoned as the indication of the deterioration status of a software product, the product can be regarded as being obsolete. Longer the time, better the maintainability would be.
机译:软件可维护性是评估软件产品的软件发展过程中的一个重要方面。由于跟踪维护行为的复杂性,很难在交付软件产品后准确预测维护成本和维护风险。为了定量解决此问题,给定软件产品交付时的健康指数,软件可维护性被视为由维护行为驱动的必然演变过程。隐马尔可夫模型(HMM)用于模拟显示为可能发生概率的维护行为。软件度量标准是对软件产品质量的度量,并且将其对交付产品的度量结果进行组合以形成产品的健康指数。健康指数是随着时间推移维护行为过程的权重。当维护行为的发生概率达到一定数量(该数量被认为是软件产品的劣化状态的指示)时,可以认为该产品已过时。时间越长,可维护性就会越好。

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