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首页> 外文期刊>The Journal of Systems and Software >DRank: A semi-automated requirements prioritization method based on preferences and dependencies
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DRank: A semi-automated requirements prioritization method based on preferences and dependencies

机译：DRank：一种基于偏好和依赖关系的半自动化需求优先级排序方法

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摘要

There are many types of dependencies between software requirements, such as the contributions dependencies (Make, Some+, Help, Break, Some-, Hurt) and business dependencies modeled in the i~* framework. However, current approaches for prioritizing requirements seldom take these dependencies into consideration, because it is difficult for stakeholders to prioritize requirements considering their preferences as well as the dependencies between requirements. To make requirement prioritization more practical, a method called DRank is proposed. DRank has the following advantages: 1) a prioritization evaluation attributes tree is constructed to make the ranking criteria selection easier and more operable; 2) RankBoost is employed to calculate the subjective requirements prioritization according to stakeholder preferences, which reduces the difficulty of evaluating the prioritization; 3) an algorithm based on the weighted PageRank is proposed to analyze the dependencies between requirements, allowing the objective dependencies to be automatically transformed into partial order relations; and 4) an integrated requirements prioritization method is developed to amend the stakeholders' subjective preferences with the objective requirements dependencies and make the process of prioritization more reasonable and applicable. A controlled experiment performed to validate the effectiveness of DRank based on comparisons with Case Based Ranking, Analytical Hierarchy Process, and EVOLVE. The results demonstrate that DRank is less time-consuming and more effective than alternative approaches. A simulation experiment demonstrates that taking requirement dependencies into consideration can improve the accuracy of the final prioritization sequence.
机译：软件需求之间有许多类型的依赖关系，例如贡献依赖关系（Make，Some +，Help，Break，Some-，Hurt）和在i〜*框架中建模的业务依赖关系。但是，当前用于对需求进行优先级排序的方法很少考虑这些依赖性，因为利益相关者很难考虑其偏好以及需求之间的依赖性来对需求进行优先级排序。为了使需求优先排序更加实用，提出了一种称为DRank的方法。 DRank具有以下优点：1）构造优先级评估属性树，以使排名标准的选择更加容易和可操作； 2）采用RankBoost根据利益相关者的偏好来计算主观需求优先级，从而降低了评估优先级的难度。 3）提出了一种基于加权PageRank的算法来分析需求之间的依赖关系，使目标依赖关系自动转换为偏序关系。 4）开发了一种综合的需求优先排序方法，以客观的需求依赖关系来修正利益相关者的主观偏好，并使优先排序过程更加合理和适用。通过与基于案例的排名，分析层次结构过程和EVOLVE进行比较，进行了一项对照实验来验证DRank的有效性。结果表明，DRank比替代方法更省时，更有效。仿真实验表明，考虑需求依赖性可以提高最终优先级排序序列的准确性。

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